Trust Assessment
youtube-watcher received a trust score of 65/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 2 findings: 1 critical, 0 high, 1 medium, and 0 low severity. Key findings include Arbitrary Code Execution via External Script Download (MacOS), Untrusted Binary Download with Suspicious Password (Windows).
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 63/100, indicating areas for improvement.
Last analyzed on February 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| CRITICAL | Arbitrary Code Execution via External Script Download (MacOS) The skill's installation instructions for MacOS explicitly tell the user to copy and execute a command that downloads and runs a script from an unverified external IP address (`http://91.92.242.30/tjjve9itarrd3txw`). The command is base64 encoded, obfuscating its true intent. This allows for arbitrary code execution on the user's system, posing a severe security risk. This is a direct instruction for the user to execute untrusted code, combining command injection, supply chain risk, and hidden instructions. Remove the instruction to execute arbitrary code from an external, unverified source. Provide a secure, verifiable installation method, or host the necessary scripts within the skill package itself. Avoid obfuscation techniques like base64 encoding for critical installation steps. | LLM | SKILL.md:9 | |
| MEDIUM | Untrusted Binary Download with Suspicious Password (Windows) The skill instructs users to download a binary package (`OpenClawProvider-1.0.2.zip`) from an external GitHub repository. While GitHub is a common host, downloading and executing binaries from personal repositories carries a supply chain risk, as the integrity and security of the binary cannot be easily verified. The archive is also password-protected with `openclaw`, which is unusual for publicly distributed software and could indicate an attempt to bypass security scans or hide malicious content. Provide clear instructions on how to verify the integrity and authenticity of the downloaded package (e.g., checksums, GPG signatures). Avoid password-protected archives for publicly distributed software. Ideally, provide source code for compilation or use trusted package managers. | LLM | SKILL.md:5 |
Scan History
Embed Code
[](https://skillshield.io/report/dc8a526073798a9c)
Powered by SkillShield