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Security Audit

slopesniper

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
68
CAUTION
Scanned 3 months ago
0
Critical
Immediate action required
2
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

slopesniper received a trust score of 68/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 3 findings: 0 critical, 2 high, 1 medium, and 0 low severity. Key findings include Skill instructs LLM to expose user's private key, Skill instructs LLM to post sensitive diagnostic data to public GitHub issues, Unpinned Git dependency in manifest.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 63/100, 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
100%
Static Code Analysis
100%
Dependency Graph
100%
LLM Behavioral Safety
63%

Behavioral Risk Signals

Network Access
2 findings
Shell Execution
2 findings

Security Findings3

SeverityFindingLayerLocation

Scan History

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