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Security Audit

network-scanner

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
20
CRITICAL
Scanned about 2 months ago
2
Critical
Immediate action required
2
High
Priority fixes suggested
0
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

network-scanner received a trust score of 20/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 4 findings: 2 critical, 2 high, 0 medium, and 0 low severity. Key findings include Arbitrary command execution, Dangerous call: subprocess.run(), Command Injection via DNS server parameter.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 55/100, indicating areas for improvement.

Last analyzed on February 12, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
70%
Static Code Analysis
85%
Dependency Graph
100%
LLM Behavioral Safety
55%

Behavioral Risk Signals

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

Security Findings4

SeverityFindingLayerLocation

Scan History

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