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Security Audit

mxe

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
55
CAUTION
Scanned 3 months ago
0
Critical
Immediate action required
3
High
Priority fixes suggested
1
Medium
Best practices review
2
Low
Acknowledged / Tracked

Trust Assessment

mxe received a trust score of 55/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 6 findings: 0 critical, 3 high, 1 medium, and 2 low severity. Key findings include Missing required field: name, Node lockfile missing, Potential Data Exfiltration via Clipboard.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 53/100, 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
93%
Dependency Graph
98%
LLM Behavioral Safety
53%

Behavioral Risk Signals

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

Security Findings6

SeverityFindingLayerLocation

Scan History

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