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Security Audit

phantom

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
35
CRITICAL
Scanned about 2 months ago
2
Critical
Immediate action required
3
High
Priority fixes suggested
0
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

phantom received a trust score of 35/100, 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, 3 high, 0 medium, and 1 low severity. Key findings include Network egress to untrusted endpoints, Unpinned remote script execution during installation, Untrusted source for critical dependency installation script.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 23/100, 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
70%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
23%

Behavioral Risk Signals

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

Security Findings6

SeverityFindingLayerLocation

Scan History

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