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Security Audit

notebooklm

github.com/davila7/claude-code-templates
AI SkillCommit 458b11867eae
10
CRITICAL
Scanned 2 months ago
8
Critical
Immediate action required
10
High
Priority fixes suggested
3
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

notebooklm received a trust score of 10/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 22 findings: 8 critical, 10 high, 3 medium, and 1 low severity. Key findings include Arbitrary command execution, Dangerous call: subprocess.run(), Network egress to untrusted endpoints.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 0/100, 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
0%
Static Code Analysis
0%
Dependency Graph
100%
LLM Behavioral Safety
56%

Behavioral Risk Signals

Network Access
3 findings
Shell Execution
20 findings

Security Findings22

SeverityFindingLayerLocation

Scan History

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