Trust Assessment
cv-pipeline-builder 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 Increment ID.
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 Increment ID The skill defines commands like `/ml:cv-evaluate <increment_id>` and `/ml:cv-deploy <increment_id>`. If the backend implementation of these commands uses the provided `<increment_id>` directly in a shell command without proper sanitization, it could lead to command injection. An attacker could craft a malicious increment ID (e.g., `0042; rm -rf /`) to execute arbitrary commands on the host system. Ensure that all user-provided or dynamically generated parameters, especially increment IDs, are strictly validated and sanitized before being used in any shell commands or subprocess calls. Prefer using argument lists for `subprocess.run` instead of a single string, or escape shell metacharacters. | LLM | SKILL.md:99 |
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