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Security Audit

database-query

github.com/cisco-ai-defense/skill-scanner
AI SkillCommit de9371289c23
65
CAUTION
Scanned 9 days ago
2
Critical
Immediate action required
0
High
Priority fixes suggested
0
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

database-query received a trust score of 65/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 2 findings: 2 critical, 0 high, 0 medium, and 0 low severity. Key findings include SQL Injection in search_users function, SQL Injection in get_user_by_id function.

The analysis covered 4 layers: dependency_graph, static_code_analysis, manifest_analysis, llm_behavioral_safety. The llm_behavioral_safety layer scored lowest at 40/100, indicating areas for improvement.

Last analyzed on February 11, 2026 (commit de937128). 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
40%

Behavioral Risk Signals

Shell Execution
2 findings
Dynamic Code
2 findings
Excessive Permissions
1 finding

Security Findings2

SeverityFindingLayerLocation

Scan History

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