sora-2-nature-documentary
Verdict safe, but 4 findings (4 low), mainly social engineering, policy violation, unauthorized tool use. Most recent scan 2026-02-07.
This skill package is SAFE for use with only minor documentation and completeness issues. No security threats were identified. The skill appears to be a simple prompt template for generating nature documentary videos using OpenAI Sora 2, with no data exfiltration, command injection, prompt injection, or other malicious behavior. The main issues are: (1) missing optional metadata fields that would improve clarity, (2) an incomplete prompt template that appears truncated, and (3) a non-functional placeholder script. None of these issues pose security risks to users or the agent system. The skill does not access sensitive files, make network calls, execute arbitrary commands, or attempt to manipulate the agent's behavior.
Scanner's overall assessment (LLM analyzer)
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Create nature documentary videos using OpenAI Sora 2. Use when generating wildlife footage, nature scenes, or educational documentary-style videos with cinematic quality.
- Package
- 4 files, 4.1 KB
- SKILL.md
- 219 words, 9 sections
- Code
- Python (1)
SKILL.md covers: Sora 2 - 自然纪录片 · 描述 · 类型 · Prompt · 特性 · Sora 2 相关特性 · 使用建议 · 参数调整 · 最佳实践
Findings
LOW Skill does not specify a license Policy Violationstatic
Skill manifest does not include a 'license' field. Specifying a license helps users understand usage terms.
SKILL.md
LOW Missing Critical Metadata Fields Social Engineeringllm
The skill manifest is missing several important metadata fields including 'license', 'compatibility', and 'allowed-tools'. While 'allowed-tools' is optional per the agent skills specification, its absence means there are no declared restrictions on what agent tools this skill can use. The missing 'license' field creates uncertainty about usage rights, and missing 'compatibility' information leaves users unclear about where this skill can be used.
SKILL.md
YAML Manifest shows:
- license: Not specified
- compatibility: Not specified
- allowed-tools: Not specifiedLOW Incomplete Prompt Template Social Engineeringllm
The prompt template in the instruction body appears to be truncated mid-sentence, ending with 'The video quality should be 4K with 60fps, with stunning cinematogr'. This incomplete instruction could lead to confusion or unexpected behavior when the skill is used. While not a security threat, it represents misleading or inaccurate content that could affect skill functionality.
SKILL.md:18
Prompt ends with: '...with stunning cinematogr' (appears cut off)LOW Non-Functional Placeholder Script Unauthorized Tool Usellm
The included Python script (scripts/example.py) is a non-functional placeholder that only prints a message and contains TODO comments. While not malicious, this represents a form of tool misrepresentation where the skill package includes a script file that serves no actual purpose. The script does not implement any functionality related to Sora 2 video generation or nature documentary creation.
scripts/example.py
Script contains only:
```python
def main():
print("This is an example script for sora-2-nature-documentary")
# TODO: Add actual script logic here
```What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 1.7 KB |
assets/example_asset.txt | doc | 865 B |
references/api_reference.md | doc | 976 B |
scripts/example.py | script | 609 B |
Package contents recorded 2026-10-22. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Llm analyzer. A language model reads the skill and reports intent-level issues the rules cannot express.
- Meta analyzer. A second model pass that validates, deduplicates and re-scores the other analyzers' findings.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://clawhub.ai/skills/sora-2-nature-documentary
- Raw scan result: sora-2-自然纪录片-scan.json
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