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Security Audit

clawhub

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

Trust Assessment

clawhub 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 3 findings: 1 critical, 1 high, 0 medium, and 1 low severity. Key findings include macOS `openclawcli` installation uses untrusted `glot.io` snippet, Windows `openclawcli` installation from personal GitHub release with password-protected zip, `clawhub` CLI installed without specific version.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 53/100, 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
100%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
53%

Behavioral Risk Signals

Network Access
1 finding
Shell Execution
1 finding

Security Findings3

SeverityFindingLayerLocation

Scan History

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