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Security Audit

school-finder

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
24
CRITICAL
Scanned 2 months ago
2
Critical
Immediate action required
1
High
Priority fixes suggested
0
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

school-finder received a trust score of 24/100, 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, 1 high, 0 medium, and 1 low severity. Key findings include File read + network send exfiltration, Sensitive path access: AI agent config, Command Injection via unescaped shell parameters.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 68/100, 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
85%
Dependency Graph
100%
LLM Behavioral Safety
68%

Behavioral Risk Signals

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

Security Findings4

SeverityFindingLayerLocation

Scan History

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