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Security Audit

stealth-browser

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
21
CRITICAL
Scanned about 2 months ago
1
Critical
Immediate action required
2
High
Priority fixes suggested
3
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

stealth-browser received a trust score of 21/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 7 findings: 1 critical, 2 high, 3 medium, and 1 low severity. Key findings include Persistence / self-modification instructions, Potential data exfiltration: file read + network send, Arbitrary File Write via User-Controlled Screenshot Path.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 62/100, indicating areas for improvement.

Last analyzed on February 14, 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
62%

Behavioral Risk Signals

Network Access
5 findings
Filesystem Write
5 findings
Shell Execution
2 findings

Security Findings7

SeverityFindingLayerLocation

Scan History

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