Trust Assessment
vercel-optimize received a trust score of 85/100, 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 Path Traversal in Claim Extraction and Verification.
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 July 1, 2026 (commit f8a72b96). 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 | Path Traversal in Claim Extraction and Verification The `extractClaims` function extracts file paths from `rec.affectedFiles` and `rec.findingRefs` (which are generated from untrusted sub-agent outputs and codebase files) and creates `file_exists` claims. These paths are normalized using `normalizePath` which does not strip or validate directory traversal sequences (e.g., `../`). When these claims are verified by `verifyClaim` in `verify-and-regen.mjs`, it can allow an attacker to verify the existence of or read arbitrary files on the host system outside the repository root. Sanitize all extracted file paths to ensure they do not contain directory traversal sequences (e.g., by resolving them against `repoRoot` and verifying that the resolved path starts with `repoRoot`). | LLM | lib/extract-claims.mjs:37 |
Scan History
Embed Code
[](https://skillshield.io/report/56d4c15e534d3ed2)
Powered by SkillShield