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Security Audit

agentos

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
10
CRITICAL
Scanned 3 months ago
3
Critical
Immediate action required
2
High
Priority fixes suggested
5
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

agentos 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 11 findings: 3 critical, 2 high, 5 medium, and 1 low severity. Key findings include Persistence / self-modification instructions, Network egress to untrusted endpoints, Missing required field: name.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 10/100, 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
10%
Static Code Analysis
72%
Dependency Graph
100%
LLM Behavioral Safety
61%

Behavioral Risk Signals

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

Security Findings11

SeverityFindingLayerLocation

Scan History

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