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Security Audit

vibetesting

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
68
CAUTION
Scanned about 1 month ago
0
Critical
Immediate action required
0
High
Priority fixes suggested
4
Medium
Best practices review
2
Low
Acknowledged / Tracked

Trust Assessment

vibetesting received a trust score of 68/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 7 findings: 0 critical, 0 high, 4 medium, and 2 low severity. Key findings include Unsafe deserialization / dynamic eval, Missing required field: name, Node lockfile missing.

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 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
86%
Static Code Analysis
93%
Dependency Graph
98%
LLM Behavioral Safety
91%

Behavioral Risk Signals

Network Access
2 findings
Filesystem Write
2 findings
Shell Execution
4 findings
Dynamic Code
2 findings
Excessive Permissions
1 finding

Security Findings7

SeverityFindingLayerLocation

Scan History

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