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Security Audit

frigatebird

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
65
CAUTION
Scanned about 2 months ago
1
Critical
Immediate action required
2
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

frigatebird 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 4 findings: 1 critical, 2 high, 1 medium, and 0 low severity. Key findings include Potential Command Injection via CLI arguments, Access to sensitive browser profiles and authentication tokens, Unpinned `frigatebird` npm package dependency.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 33/100, 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

Manifest Analysis
100%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
33%

Behavioral Risk Signals

Network Access
1 finding
Filesystem Write
2 findings
Shell Execution
3 findings
Dynamic Code
2 findings
Excessive Permissions
1 finding

Security Findings4

SeverityFindingLayerLocation

Scan History

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