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Security Audit

openscan

github.com/openclaw/skills
AI SkillCommit 9c1b8e80763e
10
CRITICAL
Scanned about 2 months ago
2
Critical
Immediate action required
2
High
Priority fixes suggested
1
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

openscan received a trust score of 10/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 6 findings: 2 critical, 2 high, 1 medium, and 1 low severity. Key findings include Arbitrary command execution, Unsafe deserialization / dynamic eval, Node lockfile missing.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 18/100, indicating areas for improvement.

Last analyzed on February 12, 2026 (commit 9c1b8e80). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
18%
Static Code Analysis
100%
Dependency Graph
98%
LLM Behavioral Safety
85%

Behavioral Risk Signals

Network Access
1 finding
Filesystem Write
2 findings
Shell Execution
5 findings
Dynamic Code
3 findings

Security Findings6

SeverityFindingLayerLocation

Scan History

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