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Security Audit

iblipper

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
71
CAUTION
Scanned about 2 months ago
1
Critical
Immediate action required
0
High
Priority fixes suggested
0
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

iblipper received a trust score of 71/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 2 findings: 1 critical, 0 high, 0 medium, and 1 low severity. Key findings include Command Injection via unvalidated shell arguments, User data sent to external third-party service.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 68/100, 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
68%

Behavioral Risk Signals

Network Access
2 findings
Shell Execution
2 findings
Dynamic Code
1 finding

Security Findings2

SeverityFindingLayerLocation

Scan History

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