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Security Audit

devinism

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
10
CRITICAL
Scanned about 2 months ago
3
Critical
Immediate action required
1
High
Priority fixes suggested
1
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

devinism received a trust score of 10/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 6 findings: 3 critical, 1 high, 1 medium, and 1 low severity. Key findings include Arbitrary command execution, Remote code execution: curl/wget pipe to shell, Arbitrary code execution via unverified remote script.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 46/100, 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
70%
Dependency Graph
100%
LLM Behavioral Safety
46%

Behavioral Risk Signals

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

Security Findings6

SeverityFindingLayerLocation

Scan History

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