{
  "skill_name": "hugging-face-cli",
  "skill_path": "/workspace/skills/huggingface-skills/skills/hugging-face-cli",
  "skill_directory": "/workspace/skills/huggingface-skills/skills/hugging-face-cli",
  "is_safe": true,
  "max_severity": "LOW",
  "findings_count": 5,
  "findings": [
    {
      "id": "MANIFEST_MISSING_LICENSE_c5ae9be793",
      "rule_id": "MANIFEST_MISSING_LICENSE",
      "category": "policy_violation",
      "severity": "LOW",
      "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": {
        "meta_reviewed": true
      }
    },
    {
      "id": "llm_finding_hugging-face-cli_0",
      "rule_id": "LLM_DATA_EXFILTRATION",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Missing allowed-tools Declaration",
      "description": "The skill does not declare 'allowed-tools' in its YAML manifest. While this field is optional per the agent skills specification, declaring it would improve transparency about which agent capabilities (Bash, Python, Read, Write, etc.) this skill requires. Since the skill executes Bash commands via the 'hf' CLI, it should ideally declare 'allowed-tools: [Bash]' for clarity.",
      "file_path": "SKILL.md",
      "line_number": null,
      "snippet": "allowed-tools: Not specified",
      "remediation": "Add 'allowed-tools: [Bash]' to the YAML frontmatter to explicitly declare the skill's tool requirements. This improves transparency and allows users to understand what capabilities the skill needs.",
      "analyzer": "llm",
      "metadata": {
        "model": "claude-sonnet-4-5-20250929",
        "overall_assessment": "The hugging-face-cli skill is a documentation-focused skill that provides command reference and examples for the Hugging Face CLI tool. The skill does not contain executable scripts (Python/Bash) and serves primarily as a reference guide. Security analysis reveals only minor informational issues: missing optional metadata fields (allowed-tools, license, compatibility), missing referenced files, and opportunities to enhance security guidance around token handling. No critical or high-severity threats were identified. The skill does not attempt prompt injection, data exfiltration, command injection, or other malicious behaviors. The internal reference files (references/commands.md, references/examples.md) contain legitimate documentation and examples without malicious content. Overall, this skill presents minimal security risk and functions as intended - a reference guide for Hugging Face CLI operations.",
        "primary_threats": [],
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "scanner_category": "SECURITY VIOLATION",
        "meta_reviewed": true
      }
    },
    {
      "id": "llm_finding_hugging-face-cli_1",
      "rule_id": "LLM_SOCIAL_ENGINEERING",
      "category": "social_engineering",
      "severity": "LOW",
      "title": "Missing License and Compatibility Metadata",
      "description": "The skill does not specify 'license' or 'compatibility' fields in its YAML manifest. While these are optional fields, including them would improve transparency about licensing terms and which environments (Claude.ai, Claude Code, API) the skill is designed for.",
      "file_path": "SKILL.md",
      "line_number": null,
      "snippet": "license: Not specified\ncompatibility: Not specified",
      "remediation": "Add 'license' field (e.g., 'MIT', 'Apache-2.0') and 'compatibility' field (e.g., 'Works in Claude.ai, Claude Code, API') to the YAML frontmatter to improve skill metadata completeness.",
      "analyzer": "llm",
      "metadata": {
        "model": "claude-sonnet-4-5-20250929",
        "overall_assessment": "The hugging-face-cli skill is a documentation-focused skill that provides command reference and examples for the Hugging Face CLI tool. The skill does not contain executable scripts (Python/Bash) and serves primarily as a reference guide. Security analysis reveals only minor informational issues: missing optional metadata fields (allowed-tools, license, compatibility), missing referenced files, and opportunities to enhance security guidance around token handling. No critical or high-severity threats were identified. The skill does not attempt prompt injection, data exfiltration, command injection, or other malicious behaviors. The internal reference files (references/commands.md, references/examples.md) contain legitimate documentation and examples without malicious content. Overall, this skill presents minimal security risk and functions as intended - a reference guide for Hugging Face CLI operations.",
        "primary_threats": [],
        "aitech": "AITech-2.1",
        "aitech_name": "Social Engineering",
        "aisubtech": null,
        "aisubtech_name": null,
        "scanner_category": "SOCIAL ENGINEERING",
        "meta_reviewed": true
      }
    },
    {
      "id": "llm_finding_hugging-face-cli_2",
      "rule_id": "LLM_DATA_EXFILTRATION",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Authentication Token Handling in Examples",
      "description": "The skill documentation includes examples of passing authentication tokens via command-line arguments ('hf auth login --token $HF_TOKEN'). While using environment variables is a reasonable practice, the skill should emphasize secure token handling and warn against hardcoding tokens in scripts or command history.",
      "file_path": null,
      "line_number": null,
      "snippet": "hf auth login --token $HF_TOKEN            # Non-interactive with token",
      "remediation": "Add a security note in the documentation emphasizing: (1) Never hardcode tokens in scripts, (2) Use environment variables or secure credential storage, (3) Be aware that tokens may appear in shell history when passed as command-line arguments, (4) Consider using interactive login ('hf auth login') for better security.",
      "analyzer": "llm",
      "metadata": {
        "model": "claude-sonnet-4-5-20250929",
        "overall_assessment": "The hugging-face-cli skill is a documentation-focused skill that provides command reference and examples for the Hugging Face CLI tool. The skill does not contain executable scripts (Python/Bash) and serves primarily as a reference guide. Security analysis reveals only minor informational issues: missing optional metadata fields (allowed-tools, license, compatibility), missing referenced files, and opportunities to enhance security guidance around token handling. No critical or high-severity threats were identified. The skill does not attempt prompt injection, data exfiltration, command injection, or other malicious behaviors. The internal reference files (references/commands.md, references/examples.md) contain legitimate documentation and examples without malicious content. Overall, this skill presents minimal security risk and functions as intended - a reference guide for Hugging Face CLI operations.",
        "primary_threats": [],
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "scanner_category": "SECURITY VIOLATION",
        "meta_reviewed": true
      }
    },
    {
      "id": "llm_finding_hugging-face-cli_3",
      "rule_id": "LLM_DATA_EXFILTRATION",
      "category": "data_exfiltration",
      "severity": "LOW",
      "title": "Missing Referenced Files",
      "description": "The skill references several files (cache.py, Repo.py, templates/examples.md, templates/commands.md, assets/examples.md, assets/commands.md) that were not found in the skill package. While two reference files (references/commands.md, references/examples.md) exist, the missing files suggest incomplete packaging or documentation references to non-existent resources.",
      "file_path": null,
      "line_number": null,
      "snippet": "Referenced files not found: cache.py, Repo.py, templates/examples.md, templates/commands.md, assets/examples.md, assets/commands.md",
      "remediation": "Either: (1) Include the missing files in the skill package if they are intended to be part of the skill, or (2) Remove references to non-existent files from the documentation to avoid confusion.",
      "analyzer": "llm",
      "metadata": {
        "model": "claude-sonnet-4-5-20250929",
        "overall_assessment": "The hugging-face-cli skill is a documentation-focused skill that provides command reference and examples for the Hugging Face CLI tool. The skill does not contain executable scripts (Python/Bash) and serves primarily as a reference guide. Security analysis reveals only minor informational issues: missing optional metadata fields (allowed-tools, license, compatibility), missing referenced files, and opportunities to enhance security guidance around token handling. No critical or high-severity threats were identified. The skill does not attempt prompt injection, data exfiltration, command injection, or other malicious behaviors. The internal reference files (references/commands.md, references/examples.md) contain legitimate documentation and examples without malicious content. Overall, this skill presents minimal security risk and functions as intended - a reference guide for Hugging Face CLI operations.",
        "primary_threats": [],
        "aitech": "AITech-8.2",
        "aitech_name": "Data Exfiltration / Exposure",
        "aisubtech": "AISubtech-8.2.3",
        "aisubtech_name": "Data Exfiltration via Agent Tooling",
        "scanner_category": "SECURITY VIOLATION",
        "meta_reviewed": true
      }
    }
  ],
  "scan_duration_seconds": 732.1405034065247,
  "duration_ms": 732140,
  "analyzers_used": [
    "static_analyzer",
    "llm_analyzer",
    "meta_analyzer"
  ],
  "timestamp": "2026-02-07T22:25:04.553113"
}