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Security Audit

osori

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
52
CAUTION
Scanned 3 months ago
1
Critical
Immediate action required
0
High
Priority fixes suggested
3
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

osori received a trust score of 52/100, 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: 1 critical, 0 high, 3 medium, and 0 low severity. Key findings include Sensitive environment variable access: $HOME, Command Injection via unsanitized root directory in scan-projects.sh.

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 12, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
79%
Dependency Graph
100%
LLM Behavioral Safety
70%

Behavioral Risk Signals

Shell Execution
4 findings
Dynamic Code
1 finding
Excessive Permissions
3 findings

Security Findings4

SeverityFindingLayerLocation

Scan History

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