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Security Audit

sundial-org/awesome-openclaw-skills:skills/alpha-finder

github.com/sundial-org/awesome-openclaw-skills
AI SkillCommit 6d998e005da6
26
CRITICAL
Scanned 27 days ago
0
Critical
Immediate action required
2
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

sundial-org/awesome-openclaw-skills:skills/alpha-finder received a trust score of 26/100, 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: 0 critical, 2 high, 2 medium, and 0 low severity. Key findings include Sensitive environment variable access: $HOME, Unpinned External Dependency via npx, Potential Command Injection via User Input to External Tool.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Static Code Analysis layer scored lowest at 56/100, indicating areas for improvement.

Last analyzed on March 3, 2026 (commit 6d998e00). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
56%
Dependency Graph
100%
LLM Behavioral Safety
100%

Behavioral Risk Signals

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

Security Findings4

SeverityFindingLayerLocation

Scan History

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