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Security Audit

sglang

github.com/davila7/claude-code-templates
AI SkillCommit 458b11867eae
53
CAUTION
Scanned about 2 months ago
0
Critical
Immediate action required
2
High
Priority fixes suggested
2
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

sglang received a trust score of 53/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 5 findings: 0 critical, 2 high, 2 medium, and 1 low severity. Key findings include Network egress to untrusted endpoints, Covert behavior / concealment directives, Unpinned dependency in manifest.

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

Last analyzed on February 12, 2026 (commit 458b1186). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
91%
Static Code Analysis
63%
Dependency Graph
100%
LLM Behavioral Safety
100%

Behavioral Risk Signals

Network Access
2 findings
Shell Execution
1 finding

Security Findings5

SeverityFindingLayerLocation

Scan History

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