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Security Audit

omi-me

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
60
CAUTION
Scanned 3 months ago
0
Critical
Immediate action required
1
High
Priority fixes suggested
4
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

omi-me received a trust score of 60/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 5 findings: 0 critical, 1 high, 4 medium, and 0 low severity. Key findings include Sensitive environment variable access: $HOME, Command Injection via jq filter, JSON Injection via unescaped user input in curl payload.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.

Last analyzed on February 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
86%
Dependency Graph
100%
LLM Behavioral Safety
71%

Behavioral Risk Signals

Network Access
2 findings
Shell Execution
5 findings
Dynamic Code
3 findings
Excessive Permissions
2 findings

Security Findings5

SeverityFindingLayerLocation

Scan History

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