Trust Assessment
aegis-security-hackathon received a trust score of 91/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 1 medium, and 1 low severity. Key findings include Node lockfile missing, Unpinned dependencies in installation instructions.
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 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 | |
|---|---|---|---|---|
| MEDIUM | Unpinned dependencies in installation instructions The skill's quick start guide recommends installing `@x402/fetch` and `@x402/evm` without specifying exact versions. This can lead to installing a vulnerable or incompatible version if a new release introduces breaking changes or security flaws, or if a malicious version is published under the same package name. Recommend pinning dependency versions (e.g., `npm install @x402/fetch@1.2.3 @x402/evm@4.5.6`) or using a lock file to ensure reproducible and secure installations. | LLM | SKILL.md:20 | |
| LOW | Node lockfile missing package.json is present but no lockfile was found (package-lock.json, pnpm-lock.yaml, or yarn.lock). Commit a lockfile for deterministic dependency resolution. | Dependencies | skills/swiftadviser/aegis-security-hackathon/package.json |
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