Trust Assessment
claw-admin received a trust score of 90/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via unsanitized user input in `curl` arguments.
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 unsanitized user input in `curl` arguments The skill documentation provides `curl` command examples where user-controlled inputs (`DESIRED_PREFIX` and `PREFIX`) are directly inserted into the URL path of shell commands. If the LLM constructs and executes these commands by directly concatenating user input without proper shell escaping or URL encoding, a malicious user could inject shell metacharacters (e.g., `;`, `|`, `&`, `$(...)`) to execute arbitrary commands on the host system. This risk applies to all `curl` commands that use `DESIRED_PREFIX` or `PREFIX` in the URL path. The LLM integration layer must ensure all user-provided inputs (`DESIRED_PREFIX`, `PREFIX`) are strictly validated (e.g., against a regex for valid email prefixes) and/or properly shell-escaped and URL-encoded before being used in `curl` commands. For JSON payloads, ensure the input is properly JSON-encoded. | LLM | SKILL.md:30 |
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