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Security Audit

backboard

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
60
CAUTION
Scanned about 2 months ago
1
Critical
Immediate action required
0
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

backboard received a trust score of 60/100, 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: 1 critical, 0 high, 2 medium, and 0 low severity. Key findings include Unpinned Python dependency version, Flask Debug Mode Enabled in Deployment Script, Broad File Type Acceptance for Document Uploads.

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
93%
LLM Behavioral Safety
63%

Behavioral Risk Signals

Filesystem Write
1 finding
Shell Execution
2 findings
Excessive Permissions
1 finding

Security Findings3

SeverityFindingLayerLocation

Scan History

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