Trust Assessment
youtube-pro received a trust score of 88/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via External Tool Execution.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Potential Command Injection via External Tool Execution The skill description indicates the use of external command-line tools `yt-dlp` and `ffmpeg`. If user-provided input (e.g., URLs, segment parameters, file paths) is directly incorporated into shell commands for these tools without proper sanitization or escaping, it could lead to command injection. An attacker could then execute arbitrary commands on the host system. This also implies a risk of excessive permissions if the skill's execution environment allows arbitrary command execution for these tools. Implement robust input validation and sanitization for all user-provided data used in constructing commands for `yt-dlp` and `ffmpeg`. Prefer using libraries or APIs that abstract shell execution, or ensure all arguments are properly escaped (e.g., using `shlex.quote` in Python) before passing them to `subprocess.run` or similar functions. Ensure the execution environment is sandboxed with minimal necessary permissions to limit the impact of any potential injection. | LLM | SKILL.md:23 |
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