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Security Audit

olvid-channel

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
60
CAUTION
Scanned 3 months ago
0
Critical
Immediate action required
2
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

olvid-channel 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 4 findings: 0 critical, 2 high, 2 medium, and 0 low severity. Key findings include Cross-skill / cross-tool manipulation, Unpinned npm dependency version, Potential Data Exfiltration via Arbitrary File Send.

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
85%
Static Code Analysis
100%
Dependency Graph
93%
LLM Behavioral Safety
78%

Behavioral Risk Signals

Network Access
2 findings
Filesystem Write
2 findings
Dynamic Code
1 finding

Security Findings4

SeverityFindingLayerLocation

Scan History

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