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Security Audit

clawhub

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
35
CRITICAL
Scanned 2 months ago
2
Critical
Immediate action required
1
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

clawhub received a trust score of 35/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 5 findings: 2 critical, 1 high, 2 medium, and 0 low severity. Key findings include Network egress to untrusted endpoints, macOS installation relies on untrusted, dynamic glot.io script, Windows installation relies on unpinned 'latest' GitHub release.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 41/100, 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
70%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
41%

Behavioral Risk Signals

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

Security Findings5

SeverityFindingLayerLocation

Scan History

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