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Security Audit

agent-republic

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
67
CAUTION
Scanned about 1 month ago
0
Critical
Immediate action required
2
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

agent-republic received a trust score of 67/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 3 findings: 0 critical, 2 high, 1 medium, and 0 low severity. Key findings include Credentials file path override via environment variable, Shell command injection in bot status/verify commands, JSON injection via direct string interpolation in API calls.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 63/100, 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
63%

Behavioral Risk Signals

Network Access
2 findings
Filesystem Write
2 findings
Shell Execution
3 findings
Dynamic Code
2 findings

Security Findings3

SeverityFindingLayerLocation

Scan History

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