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Security Audit

can

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
65
CAUTION
Scanned 3 months ago
12
Critical
Immediate action required
0
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

can 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 13 findings: 12 critical, 0 high, 1 medium, and 0 low severity. Key findings include Potential Command Injection via Unsanitized Input in Shell Commands, Handling of Sensitive Private Keys.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 0/100, 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
0%

Behavioral Risk Signals

Filesystem Write
12 findings
Shell Execution
13 findings
Dynamic Code
12 findings
Excessive Permissions
1 finding

Security Findings13

SeverityFindingLayerLocation

Scan History

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