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Security Audit

functions

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
38
CRITICAL
Scanned about 2 months ago
2
Critical
Immediate action required
0
High
Priority fixes suggested
0
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

functions received a trust score of 38/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 3 findings: 2 critical, 0 high, 0 medium, and 1 low severity. Key findings include Network egress to untrusted endpoints, Recommendation to store credentials in .env without security guidance.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 40/100, indicating areas for improvement.

Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
40%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
98%

Behavioral Risk Signals

Network Access
2 findings
Filesystem Write
1 finding
Shell Execution
1 finding

Security Findings3

SeverityFindingLayerLocation

Scan History

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