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Security Audit

clawtter

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
62
CAUTION
Scanned 2 months ago
3
Critical
Immediate action required
0
High
Priority fixes suggested
0
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

clawtter received a trust score of 62/100, 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: 3 critical, 0 high, 0 medium, and 1 low severity. Key findings include Node lockfile missing, Unsafe variable interpolation in JSON payload allows command injection, Unsafe variable interpolation in URL allows command injection.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 10/100, 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
98%
LLM Behavioral Safety
10%

Behavioral Risk Signals

Network Access
3 findings
Filesystem Write
2 findings
Shell Execution
3 findings
Dynamic Code
3 findings

Security Findings4

SeverityFindingLayerLocation

Scan History

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