{
  "skill_name": "media-use",
  "skill_path": "/Users/brianlevine/claude-projects/skill-scanner-test/skills/heygen-com-hyperframes/skills/media-use",
  "is_safe": false,
  "max_severity": "CRITICAL",
  "findings_count": 116,
  "findings": [
    {
      "id": "LOW_ANALYZABILITY_MODERATE",
      "rule_id": "LOW_ANALYZABILITY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Moderate analyzability score",
      "description": "Only 80% of skill content could be analyzed. 19 of 116 files are opaque to the scanner. Some content could not be verified as safe.",
      "file_path": null,
      "line_number": null,
      "snippet": null,
      "remediation": "Review opaque files and replace with inspectable formats where possible.",
      "analyzer": "analyzability",
      "metadata": {
        "score": 80.0,
        "unanalyzable_files": 19,
        "total_files": 116,
        "risk_level": "MEDIUM",
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "EXCESSIVE_FILE_COUNT_b4d159c0e3",
      "rule_id": "EXCESSIVE_FILE_COUNT",
      "category": "policy_violation",
      "severity": "LOW",
      "title": "Skill package contains many files",
      "description": "Skill package contains 116 files. Large file counts increase attack surface and may indicate bundled dependencies or unnecessary content.",
      "file_path": ".",
      "line_number": null,
      "snippet": null,
      "remediation": "Review file inventory and remove unnecessary files.",
      "analyzer": "static",
      "metadata": {
        "file_count": 116,
        "type_breakdown": {
          "other": 3,
          "markdown": 25,
          "javascript": 65,
          "python": 4,
          "binary": 19
        },
        "aitech": null,
        "aitech_name": null,
        "aisubtech": null,
        "aisubtech_name": null,
        "aitech_mappings": [],
        "aisubtech_mappings": [],
        "framework_mappings": [],
        "taxonomy_status": "not_applicable",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "MANIFEST_MISSING_LICENSE_c5ae9be793",
      "rule_id": "MANIFEST_MISSING_LICENSE",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Skill does not specify a license",
      "description": "Skill manifest does not include a 'license' field. Specifying a license helps users understand usage terms.",
      "file_path": "SKILL.md",
      "line_number": null,
      "snippet": null,
      "remediation": "Add 'license' field to SKILL.md frontmatter (e.g., MIT, Apache-2.0)",
      "analyzer": "static",
      "metadata": {
        "aitech": null,
        "aitech_name": null,
        "aisubtech": null,
        "aisubtech_name": null,
        "aitech_mappings": [],
        "aisubtech_mappings": [],
        "framework_mappings": [],
        "taxonomy_status": "not_applicable",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/chime.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/chime.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/chime.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.737088866063676,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_5e05b6cfc6",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/chime.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/chime.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/chime.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/click-soft.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/click-soft.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/click-soft.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 13.514467502819269,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_b07f412a0b",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/click-soft.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/click-soft.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/click-soft.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/click.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/click.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/click.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 13.514467502819269,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_71c2f7ccae",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/click.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/click.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/click.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/error.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/error.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/error.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 15.661416265450615,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_b3d07bd330",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/error.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/error.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/error.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/glitch-1.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/glitch-1.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/glitch-1.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.365416830340155,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_a25764405f",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/glitch-1.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/glitch-1.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/glitch-1.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/glitch-2.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/glitch-2.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/glitch-2.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.774787059601174,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_5a053fcc5f",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/glitch-2.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/glitch-2.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/glitch-2.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/glitch-3.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/glitch-3.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/glitch-3.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.596189756144412,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_4afb6e46b2",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/glitch-3.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/glitch-3.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/glitch-3.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/impact-bass-1.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/impact-bass-1.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/impact-bass-1.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.047059991671503,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_77c5066471",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/impact-bass-1.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/impact-bass-1.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/impact-bass-1.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/impact-bass-2.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/impact-bass-2.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/impact-bass-2.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.339850002884624,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_550f88c6cb",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/impact-bass-2.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/impact-bass-2.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/impact-bass-2.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/key-press.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/key-press.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/key-press.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 11.93258386928929,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_2239b441ea",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/key-press.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/key-press.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/key-press.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/notification.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/notification.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/notification.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 16.26180110719531,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_ddd0b1ecc2",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/notification.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/notification.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/notification.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/ping.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/ping.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/ping.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.688250309133178,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_039fac6f5e",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/ping.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/ping.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/ping.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/pop.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/pop.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/pop.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.491853096329674,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_a553d070e7",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/pop.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/pop.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/pop.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/riser.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/riser.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/riser.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 18.29232163280204,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_f616f95d60",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/riser.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/riser.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/riser.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/sparkle.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/sparkle.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/sparkle.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 15.815733519161004,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_e4c8ad1db9",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/sparkle.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/sparkle.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/sparkle.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/typing.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/typing.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/typing.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.712741927075735,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_f4c9a0b190",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/typing.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/typing.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/typing.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/whoosh-cinematic.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/whoosh-cinematic.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/whoosh-cinematic.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 17.436711542137214,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_f6a2bb3f1a",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/whoosh-cinematic.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/whoosh-cinematic.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/whoosh-cinematic.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/whoosh-short.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/whoosh-short.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/whoosh-short.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.1666338592993,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_80776761be",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/whoosh-short.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/whoosh-short.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/whoosh-short.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNANALYZABLE_BINARY_audio/assets/sfx/whoosh.mp3",
      "rule_id": "UNANALYZABLE_BINARY",
      "category": "policy_violation",
      "severity": "MEDIUM",
      "title": "Unanalyzable binary file",
      "description": "Binary file 'audio/assets/sfx/whoosh.mp3' cannot be inspected by the scanner. Reason: Binary file (.mp3) - cannot inspect content. Binary files resist static analysis and may contain hidden functionality.",
      "file_path": "audio/assets/sfx/whoosh.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Replace binary files with source code, or submit the binary to VirusTotal for independent verification (--use-virustotal).",
      "analyzer": "analyzability",
      "metadata": {
        "skip_reason": "Binary file (.mp3) - cannot inspect content",
        "weight": 14.1666338592993,
        "semantic_facts": {
          "evidence_kind": "file_analyzability",
          "evidence_value_class": "opaque_binary",
          "context_kind": "binary",
          "signal_kind": "unanalyzable_binary"
        },
        "cel": {
          "decision": "would_suppress",
          "reason": "shadow_or_rule_rollout",
          "fact_schema": "v1",
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "BINARY_FILE_DETECTED_55de1c51ed",
      "rule_id": "BINARY_FILE_DETECTED",
      "category": "policy_violation",
      "severity": "INFO",
      "title": "Binary file detected in skill package",
      "description": "Binary file found: audio/assets/sfx/whoosh.mp3. Binary files cannot be inspected by static analysis. Consider using Python or Bash scripts for transparency.",
      "file_path": "audio/assets/sfx/whoosh.mp3",
      "line_number": null,
      "snippet": null,
      "remediation": "Review binary file necessity. Replace with auditable scripts if possible.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "file_inventory",
          "context_kind": "binary",
          "signals": [
            {
              "rule_id": "BINARY_FILE_DETECTED",
              "kind": "unanalyzable_binary",
              "file_path": "audio/assets/sfx/whoosh.mp3",
              "value_class": "binary"
            }
          ]
        },
        "aitech": "AITech-9.2",
        "aitech_name": "Detection Evasion",
        "aisubtech": "AISubtech-9.2.1",
        "aisubtech_name": "Obfuscation Vulnerabilities",
        "aitech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "MITRE ATLAS: AML.T0107: Exploitation for Defense Evasion",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "framework_mappings": [
          "OWASP: LLM09:2026: Vector and Embedding Weaknesses",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "MITRE ATLAS: AML.T0074: Masquerading",
          "MITRE ATLAS: AML.T0068: LLM Prompt Obfuscation",
          "NIST AML: N/A",
          "Cisco AI MDL Code: MDL-001",
          "Cisco AI MDL Code: MDL-003",
          "Cisco AI MDL Code: MDL-009",
          "Cisco AI MDL Code: MDL-011",
          "Cisco AI MDL Code: MDL-016",
          "Cisco AI MDL Code: MDL-017",
          "Cisco AI MDL Code: MDL-019"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_d4ff9875be",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/audio.test.mjs",
      "line_number": 4,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/audio.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/audio.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_953dde759c",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/audio.test.mjs",
      "line_number": 141,
      "snippet": "return spawnSync(process.execPath, [join(HERE, \"audio.mjs\"), \"--hyperframes\", dir, ...args], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 7,
        "signature_match_end": 17,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/audio.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/audio.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_799755fd08",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/carve.mjs",
      "line_number": 27,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/carve.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/carve.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_1aa237a924",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/carve.test.mjs",
      "line_number": 3,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/carve.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/carve.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_68ded0a588",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/gemini-pipeline.test.mjs",
      "line_number": 6,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_84b84628d7",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'generativelanguage.googleapis.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/gemini-pipeline.test.mjs",
      "line_number": 38,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_5677dd15ba",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/gemini-pipeline.test.mjs",
      "line_number": 60,
      "snippet": "fs.writeFileSync(path.join(args[args.indexOf('--dir')+1], 'transcript.json'), JSON.stringify([",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 0,
        "signature_match_end": 17,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_3457dda21d",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/gemini-pipeline.test.mjs",
      "line_number": 78,
      "snippet": "const result = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/gemini-pipeline.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_d4501807c8",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/heygen-tts.test.mjs",
      "line_number": 3,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/heygen-tts.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/heygen-tts.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_a214debb9b",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/heygen-tts.test.mjs",
      "line_number": 17,
      "snippet": "const run = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 12,
        "signature_match_end": 22,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/heygen-tts.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/heygen-tts.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_0cbf11448e",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'api.heygen.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/heygen-voice.test.mjs",
      "line_number": 35,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/heygen-voice.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_f97169080d",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/audio-meta.test.mjs",
      "line_number": 14,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/audio-meta.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/audio-meta.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_a06ab70631",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/audio-meta.test.mjs",
      "line_number": 110,
      "snippet": "const result = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/audio-meta.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/audio-meta.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_34d6d821da",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/bgm.mjs",
      "line_number": 14,
      "snippet": "import { spawn, spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 28,
        "signature_match_end": 53,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_dacf2d3d9e",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/bgm.mjs",
      "line_number": 35,
      "snippet": "return spawnSync(cmd, args, { stdio: \"ignore\" }).status === 0;",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 7,
        "signature_match_end": 17,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_75bd82823b",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/bgm.mjs",
      "line_number": 45,
      "snippet": "return spawnSync(cmd, args, { stdio: \"ignore\" }).status === 0;",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 7,
        "signature_match_end": 17,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_EVAL_7203b9055e",
      "rule_id": "COMMAND_INJECTION_EVAL",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Dangerous code execution functions that can execute arbitrary code",
      "description": "Pattern detected: eval(",
      "file_path": "audio/scripts/lib/bgm.mjs",
      "line_number": 232,
      "snippet": "model.eval()",
      "remediation": "Avoid eval(), exec(), and compile(). Use safer alternatives like ast.literal_eval() or operator module",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "(?<!['\\\"])\\beval\\s*\\(",
        "matched_text": "eval(",
        "signature_pattern_index": 0,
        "signature_match_start": 6,
        "signature_match_end": 11,
        "signature_pattern_sha256": "965406a10c27bfbc9765905dc4e20e4e695541b28654b082352d6aea5df24b1d",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_EVAL",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_EVAL",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/bgm.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_11fcc73389",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/gemini-auth.mjs",
      "line_number": 1,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/gemini-auth.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/gemini-auth.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_d3418526f8",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'oauth2.googleapis.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/lib/gemini-auth.py",
      "line_number": 30,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/gemini-auth.py",
              "value_class": "python"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_12be4b0493",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'www.googleapis.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/lib/gemini-auth.py",
      "line_number": 34,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/gemini-auth.py",
              "value_class": "python"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_ae9eb167bc",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
      "line_number": 1,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_4aef7efe96",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
      "line_number": 84,
      "snippet": "const result = spawnSync(cmd, args, { encoding: \"utf8\", timeout: 30_000 });",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/gemini-auth.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_NETWORK_b97a362163",
      "rule_id": "DATA_EXFIL_JS_NETWORK",
      "category": "data_exfiltration",
      "severity": "MEDIUM",
      "title": "Outbound network request primitives in JavaScript/TypeScript",
      "description": "Pattern detected: fetch(",
      "file_path": "audio/scripts/lib/heygen.mjs",
      "line_number": 190,
      "snippet": "const res = await fetch(`${heygenBase()}${path}`, opts);",
      "remediation": "Ensure network operations are necessary and document allowed destinations",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bfetch\\s*\\(",
        "matched_text": "fetch(",
        "signature_pattern_index": 0,
        "signature_match_start": 18,
        "signature_match_end": 24,
        "signature_pattern_sha256": "57220410873979f73624c44365682301491cb30501bab8d40d073a07386ad701",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_NETWORK",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/heygen.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_NETWORK",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/heygen.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_c1452dbbcb",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'api-canary.heygen.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/lib/heygen.test.mjs",
      "line_number": 222,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/heygen.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_eef26acbf3",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/python.mjs",
      "line_number": 18,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/python.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/python.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_bb9562f245",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/python.mjs",
      "line_number": 26,
      "snippet": "const result = spawnSync(cmd, args, { encoding: \"utf-8\", timeout: 5000 });",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/python.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/python.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_430a0d77b0",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'freesound.org' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "audio/scripts/lib/sfx.test.mjs",
      "line_number": 142,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/sfx.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_16e188f5e8",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 3,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_46ab8d602b",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 19,
      "snippet": "const text = fs.readFileSync(input, \"utf8\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 13,
        "signature_match_end": 29,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_30c3860fd7",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 20,
      "snippet": "fs.writeFileSync(output + \".started\", input);",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 0,
        "signature_match_end": 17,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_b3bfa25f2e",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 26,
      "snippet": "const consumed = fs.readFileSync(input, \"utf8\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 17,
        "signature_match_end": 33,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_b6b0177790",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 27,
      "snippet": "fs.writeFileSync(output + \".json\", JSON.stringify({ input, text, consumed, args }));",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 0,
        "signature_match_end": 17,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_c1cb2d01a5",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 29,
      "snippet": "if (process.env.CASE_MODE !== \"no-output\") fs.writeFileSync(output, consumed);",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 43,
        "signature_match_end": 60,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_b374b8adfa",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 37,
      "snippet": "import childProcess from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 20,
        "signature_match_end": 45,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_e56f4484b7",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 44,
      "snippet": "fs.writeFileSync(join(preexisting, \"marker\"), \"keep\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 0,
        "signature_match_end": 17,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_5852b3d625",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 85,
      "snippet": "const slowInput = fs.readFileSync(slowWav + \".started\", \"utf8\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 18,
        "signature_match_end": 34,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_89d5b56e2c",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 88,
      "snippet": "assert.equal(fs.readFileSync(slowInput, \"utf8\"), \"slow\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 13,
        "signature_match_end": 29,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_938143b805",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.writeFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 90,
      "snippet": "fs.writeFileSync(process.env.RELEASE_FILE, \"release\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:writeFile|writeFileSync|createWriteStream|appendFile|appendFileSync)\\s*\\(",
        "matched_text": "fs.writeFileSync(",
        "signature_pattern_index": 1,
        "signature_match_start": 0,
        "signature_match_end": 17,
        "signature_pattern_sha256": "1c34e30145949b4bc46f0c41b5880cbd446655f506f3f944b24730bbc67adbec",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_9033862bfa",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 93,
      "snippet": "assert.equal(fs.readFileSync(slowWav, \"utf8\"), \"slow\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 13,
        "signature_match_end": 29,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_723493f9ce",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 104,
      "snippet": "assert.equal(fs.readFileSync(wavAbs, \"utf8\"), \"synthetic caf\u00e9\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 13,
        "signature_match_end": 29,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_57ea39d6c9",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 107,
      "snippet": "const log = JSON.parse(fs.readFileSync(wavAbs + \".json\", \"utf8\"));",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 23,
        "signature_match_end": 39,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_FS_ACCESS_ef65dc42ed",
      "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Node.js filesystem access candidate for sensitive-flow correlation",
      "description": "Pattern detected: fs.readFileSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 115,
      "snippet": "assert.equal(fs.readFileSync(join(preexisting, \"marker\"), \"utf8\"), \"keep\");",
      "remediation": "Review filesystem operations and correlate sensitive sources with outbound sinks",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "fs\\.(?:readFile|readFileSync|createReadStream)\\s*\\(",
        "matched_text": "fs.readFileSync(",
        "signature_pattern_index": 0,
        "signature_match_start": 13,
        "signature_match_end": 29,
        "signature_pattern_sha256": "63e5503f1d25cece59cb25665bea6890bc89867830f245f24fce5c40b2000fa7",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_FS_ACCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_a89afbe322",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
      "line_number": 129,
      "snippet": "const result = spawnSync(process.execPath, [\"--input-type=module\", \"-e\", exercise], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.cleanup.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_120333b70a",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/lib/tts.mjs",
      "line_number": 17,
      "snippet": "import { spawn, spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 28,
        "signature_match_end": 53,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_37189dfb8a",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/tts.mjs",
      "line_number": 33,
      "snippet": "const r = spawnSync(cmd, args, {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 10,
        "signature_match_end": 20,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_1267d8426c",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/tts.mjs",
      "line_number": 111,
      "snippet": "const r = spawnSync(\"ffmpeg\", [\"-i\", absPath], { encoding: \"utf8\" });",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 10,
        "signature_match_end": 20,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_53008025ca",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/tts.mjs",
      "line_number": 116,
      "snippet": "const r = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 10,
        "signature_match_end": 20,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_4fd0aeb4cb",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/lib/tts.mjs",
      "line_number": 223,
      "snippet": "const ff = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 11,
        "signature_match_end": 21,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/lib/tts.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_266cfa11d0",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "audio/scripts/wait-bgm.test.mjs",
      "line_number": 3,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/wait-bgm.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/wait-bgm.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_e3718162b8",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "audio/scripts/wait-bgm.test.mjs",
      "line_number": 87,
      "snippet": "const run = spawnSync(process.execPath, [script, ...args, \"--timeout-ms\", \"1000\"], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 12,
        "signature_match_end": 22,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "audio/scripts/wait-bgm.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "audio/scripts/wait-bgm.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_05326ef0bd",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/compatibility.test.mjs",
      "line_number": 4,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/compatibility.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/compatibility.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_9d42ce357a",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/dither.mjs",
      "line_number": 3,
      "snippet": "import { execFileSync, spawn } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 31,
        "signature_match_end": 56,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/dither.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/dither.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_c5452dee44",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/dither.test.mjs",
      "line_number": 2,
      "snippet": "import { execFileSync, spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 35,
        "signature_match_end": 60,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_4315ccf932",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/dither.test.mjs",
      "line_number": 11,
      "snippet": "spawnSync(\"ffmpeg\", [\"-version\"], { stdio: \"ignore\" }).status === 0 &&",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 0,
        "signature_match_end": 10,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_f573d23d72",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/dither.test.mjs",
      "line_number": 12,
      "snippet": "spawnSync(\"ffprobe\", [\"-version\"], { stdio: \"ignore\" }).status === 0;",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 0,
        "signature_match_end": 10,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_cdeb5ef2a7",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/dither.test.mjs",
      "line_number": 24,
      "snippet": "return spawnSync(process.execPath, [SCRIPT, ...args, \"--json\"], { encoding: \"utf8\" });",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 7,
        "signature_match_end": 17,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/dither.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_8945113d08",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/eval.mjs",
      "line_number": 18,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/eval.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/eval.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_EVAL_9d3c370e63",
      "rule_id": "COMMAND_INJECTION_EVAL",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Dangerous code execution functions that can execute arbitrary code",
      "description": "Pattern detected: exec (",
      "file_path": "scripts/lib/npx-sync.mjs",
      "line_number": 20,
      "snippet": "// execFileSync/spawnSync cannot exec (spawnSync npx ENOENT) \u2014",
      "remediation": "Avoid eval(), exec(), and compile(). Use safer alternatives like ast.literal_eval() or operator module",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "(?<!['\\\"\\.])\\bexec\\s*\\(",
        "matched_text": "exec (",
        "signature_pattern_index": 1,
        "signature_match_start": 33,
        "signature_match_end": 39,
        "signature_pattern_sha256": "6a39f8973c64f233f1186cc082332fbd67f9556cf70a62a40d294db5bd46a30b",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "prohibition",
        "signature_polarity": "negative",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "prohibition",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_EVAL",
              "kind": "signature_polarity",
              "file_path": "scripts/lib/npx-sync.mjs",
              "value_class": "negative"
            },
            {
              "rule_id": "COMMAND_INJECTION_EVAL",
              "kind": "unreferenced_executable",
              "file_path": "scripts/lib/npx-sync.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "UNDECLARED_NETWORK_DESTINATION_38b05421b5",
      "rule_id": "UNDECLARED_NETWORK_DESTINATION",
      "category": "unauthorized_tool_use",
      "severity": "LOW",
      "title": "Script contacts a destination the documentation never mentions",
      "description": "Script contacts or configures 'us.i.posthog.com' but the skill documentation never visibly mentions it. Undocumented network destinations can indicate behaviour the manifest and description do not disclose.",
      "file_path": "scripts/lib/telemetry.mjs",
      "line_number": 13,
      "snippet": null,
      "remediation": "Document the destination in SKILL.md (or the manifest description) if it is intended, or remove the undisclosed network access. Organizations can list internal hosts in llm_analysis.trusted_reference_domains.",
      "analyzer": "static",
      "metadata": {
        "semantic_facts": {
          "evidence_kind": "pattern_match",
          "context_kind": "code",
          "signals": [
            {
              "rule_id": "UNDECLARED_NETWORK_DESTINATION",
              "kind": "unreferenced_executable",
              "file_path": "scripts/lib/telemetry.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.3",
        "aisubtech_name": "Unauthorized or Unsolicited Network Access",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0049: Exploit Public Facing Application",
          "NIST AML: AML.T0072: Reverse Shell",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "DATA_EXFIL_JS_NETWORK_0175ead4be",
      "rule_id": "DATA_EXFIL_JS_NETWORK",
      "category": "data_exfiltration",
      "severity": "MEDIUM",
      "title": "Outbound network request primitives in JavaScript/TypeScript",
      "description": "Pattern detected: fetch(",
      "file_path": "scripts/lib/telemetry.mjs",
      "line_number": 163,
      "snippet": "await fetch(`${posthogHost()}/batch/`, {",
      "remediation": "Ensure network operations are necessary and document allowed destinations",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bfetch\\s*\\(",
        "matched_text": "fetch(",
        "signature_pattern_index": 0,
        "signature_match_start": 6,
        "signature_match_end": 12,
        "signature_pattern_sha256": "57220410873979f73624c44365682301491cb30501bab8d40d073a07386ad701",
        "scanner_category": "SECURITY VIOLATION",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "data_exfiltration",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "DATA_EXFIL_JS_NETWORK",
              "kind": "signature_polarity",
              "file_path": "scripts/lib/telemetry.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "DATA_EXFIL_JS_NETWORK",
              "kind": "unreferenced_executable",
              "file_path": "scripts/lib/telemetry.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "aitech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0024.000: Exfiltration via AI Inference API: Infer Training Data Membership",
          "MITRE ATLAS: AML.T0035: AI Artifact Collection",
          "MITRE ATLAS: AML.T0037: Data From Local System",
          "MITRE ATLAS: AML.T0057: LLM Data Leakage",
          "NIST AML: NISTAML.037: Training Data Attacks"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "framework_mappings": [
          "OWASP: LLM02:2026: Sensitive Information Disclosure",
          "OWASP: ASI02: Tool Misuse & Exploitation",
          "OWASP: ASI09: Human-Agent Trust Exploitation",
          "MITRE ATLAS: AML.T0086: Exfiltration via AI Agent Tool Invocation",
          "NIST AML: N/A"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_dd4ee0e5a9",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/resolve-plugin.test.mjs",
      "line_number": 2,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_3b9a748777",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/resolve-plugin.test.mjs",
      "line_number": 24,
      "snippet": "const result = spawnSync(process.execPath, [join(dir, \"resolve.mjs\"), \"--intent\", \"a & b\"], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_c860708afd",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/resolve-plugin.test.mjs",
      "line_number": 52,
      "snippet": "const result = spawnSync(process.execPath, [join(scripts, \"resolve.mjs\")], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve-plugin.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_527b4f920d",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/resolve.mjs",
      "line_number": 2,
      "snippet": "import { spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 21,
        "signature_match_end": 46,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_e09511b95d",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/resolve.mjs",
      "line_number": 16,
      "snippet": "const result = spawnSync(invocation.cmd, invocation.args, invocation.opts);",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 15,
        "signature_match_end": 25,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_ff20c71600",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/resolve.mjs",
      "line_number": 23,
      "snippet": "? spawnSync(process.execPath, [dist, \"media-use\", \"resolve\", ...process.argv.slice(2)], {",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 2,
        "signature_match_end": 12,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_5b8190a6f5",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/resolve.mjs",
      "line_number": 26,
      "snippet": ": spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 2,
        "signature_match_end": 12,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/resolve.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/resolve.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_5567e776ef",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/transcribe.mjs",
      "line_number": 3,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcribe.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcribe.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_c747ef9c7f",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/transcribe.test.mjs",
      "line_number": 2,
      "snippet": "import { execFileSync, spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 35,
        "signature_match_end": 60,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcribe.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcribe.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_fa890126c4",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/transcribe.test.mjs",
      "line_number": 91,
      "snippet": "const res = spawnSync(",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 12,
        "signature_match_end": 22,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcribe.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcribe.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_5cdb8e3738",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/transcript-cut.mjs",
      "line_number": 3,
      "snippet": "import { execFileSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 24,
        "signature_match_end": 49,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcript-cut.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcript-cut.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_b2e684969a",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: from \"node:child_process\"",
      "file_path": "scripts/transcript-cut.test.mjs",
      "line_number": 2,
      "snippet": "import { execFileSync, spawnSync } from \"node:child_process\";",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "from\\s+['\"](?:node:)?child_process['\"]",
        "matched_text": "from \"node:child_process\"",
        "signature_pattern_index": 1,
        "signature_match_start": 35,
        "signature_match_end": 60,
        "signature_pattern_sha256": "9376960e72aac8f6d944cee70e70b31657c1f32ad94358351255626f957be3d1",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_f4ffde7186",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/transcript-cut.test.mjs",
      "line_number": 11,
      "snippet": "spawnSync(\"ffmpeg\", [\"-version\"], { stdio: \"ignore\" }).status === 0 &&",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 0,
        "signature_match_end": 10,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_4bc6dcbf56",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/transcript-cut.test.mjs",
      "line_number": 12,
      "snippet": "spawnSync(\"ffprobe\", [\"-version\"], { stdio: \"ignore\" }).status === 0;",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 0,
        "signature_match_end": 10,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    },
    {
      "id": "COMMAND_INJECTION_JS_CHILD_PROCESS_90e7ddd4a0",
      "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
      "category": "command_injection",
      "severity": "CRITICAL",
      "title": "Node.js child_process module usage for shell command execution",
      "description": "Pattern detected: spawnSync(",
      "file_path": "scripts/transcript-cut.test.mjs",
      "line_number": 28,
      "snippet": "return spawnSync(process.execPath, [SCRIPT, ...args], { encoding: \"utf8\" });",
      "remediation": "Avoid child_process. If required, use execFile with explicit arguments instead of exec with shell strings",
      "analyzer": "static",
      "metadata": {
        "matched_pattern": "\\bspawnSync\\s*\\(",
        "matched_text": "spawnSync(",
        "signature_pattern_index": 4,
        "signature_match_start": 7,
        "signature_match_end": 17,
        "signature_pattern_sha256": "3c92a0ce248fd615ee0beac96446f213058d9a10f94a9a5d0965ee01598793c9",
        "scanner_category": "INJECTION ATTACK",
        "signature_context": "package",
        "signature_polarity": "active",
        "source_category": "command_injection",
        "category_normalization": "native",
        "semantic_facts": {
          "evidence_kind": "signature_pattern",
          "context_kind": "package",
          "signals": [
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "signature_polarity",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "active"
            },
            {
              "rule_id": "COMMAND_INJECTION_JS_CHILD_PROCESS",
              "kind": "unreferenced_executable",
              "file_path": "scripts/transcript-cut.test.mjs",
              "value_class": "javascript"
            }
          ]
        },
        "aitech": "AITech-9.1",
        "aitech_name": "Model or Agentic System Manipulation",
        "aisubtech": "AISubtech-9.1.4",
        "aisubtech_name": "Injection Attacks (e.g., SQL, Command Execution, XSS)",
        "aitech_mappings": [
          "OWASP: LLM04:2026: Supply Chain",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "NIST AML: NISTAML.023: Backdoor Poisoning",
          "Cisco AI MDL Code: MDL-006",
          "Cisco AI MDL Code: MDL-007",
          "Cisco AI MDL Code: MDL-005",
          "Cisco AI MDL Code: MDL-010",
          "Cisco AI MDL Code: MDL-012",
          "Cisco AI MDL Code: MDL-014",
          "Cisco AI MDL Code: MDL-015",
          "Cisco AI MDL Code: MDL-019"
        ],
        "aisubtech_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "framework_mappings": [
          "OWASP: LLM01:2026: Prompt Injection",
          "OWASP: LLM10:2026: Improper Output Handling",
          "OWASP: LLM03:2026: Excessive Agency",
          "OWASP: ASI04: Agentic Supply Chain Vulnerabilities",
          "OWASP: ASI05: Unexpected Code Execution (RCE)",
          "MITRE ATLAS: AML.T0051: LLM Prompt Injection",
          "MITRE ATLAS: AML.T0050: Command and Scripting Interpreter",
          "MITRE ATLAS: AML.T0067: LLM Trusted Output Component Manipulation",
          "MITRE ATT&CK: T1588.007: Obtain AI Capabilities",
          "NIST AML: NISTAML.024: Targeted Poisoning"
        ],
        "taxonomy_status": "mapped",
        "taxonomy_source": "rule"
      }
    }
  ],
  "scan_duration_seconds": 0.8181371688842773,
  "duration_ms": 818,
  "analyzers_used": [
    "static_analyzer",
    "bytecode",
    "pipeline",
    "correlation",
    "behavioral_analyzer",
    "trigger_analyzer"
  ],
  "timestamp": "2026-10-22T04:36:35.418210+00:00",
  "scan_metadata": {
    "policy_name": "default",
    "policy_version": "1.0",
    "policy_preset_base": "balanced",
    "policy_fingerprint_sha256": "3f48e661bfbc54597f97bbf3dcf2c1cbae2f596ddc79c0b44784efea326b3d1d",
    "cel": {
      "mode": "shadow",
      "runtime": "cel-go",
      "runtime_version": "v0.32.0;helper=2.3.1",
      "fact_schema": "v1",
      "expression_set_hash": "f26459b8f4a46a974d7ab0aaae34127b5b6a40d693e266e12fca03a69a6d26aa",
      "evaluated": 19,
      "retained": 116,
      "would_suppress": 19,
      "suppressed": 0,
      "fallbacks": 0,
      "projection_incomplete": 0,
      "elapsed_ms": 5.027,
      "projection_ms": 3.309,
      "evaluation_ms": 1.481,
      "errors": [],
      "per_rule": {
        "UNANALYZABLE_BINARY": {
          "keep": 0,
          "would_suppress": 19,
          "fallback": 0,
          "suppressed": 0,
          "expression_hash": "5a9db9ca3422a0d8437343780ce9aaabdc4dca71aa98bcf63a85b681ef985ce2",
          "pack": "core",
          "rollout": "shadow"
        }
      },
      "suppressed_candidates": []
    },
    "rule_contract": {
      "status": "passed",
      "schema_version": 2,
      "checked": 48,
      "invalid_findings": 0,
      "errors": []
    },
    "taxonomy": {
      "source": "builtin",
      "version": "2.0.0",
      "name": "Cisco AI Security and Safety Taxonomy",
      "revision": "655a343ac943a51b6f61f86e47156e7752c15dc6",
      "snapshot_sha256": "413e8ce9081e6d91b78aaa0d0b1c06cdc15d0406ad319e23e9f9f4f80735c441",
      "findings": {
        "mapped": 114,
        "not_applicable": 2,
        "unmapped": 0
      }
    }
  },
  "scanner_version": "2.3.1",
  "source": "heygen-com",
  "repo_url": "https://github.com/heygen-com/hyperframes"
}