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Security Audit

munger-observer

github.com/jdrhyne/agent-skills
AI SkillCommit 0676c56a8ab1
86
TRUSTED
Scanned about 2 months ago
0
Critical
Immediate action required
0
High
Priority fixes suggested
2
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

munger-observer received a trust score of 86/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 2 medium, and 0 low severity. Key findings include Potential Path Traversal in Memory File Access, Vague Log Scanning Poses Data Exfiltration/Command Injection Risk.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.

Last analyzed on February 11, 2026 (commit 0676c56a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
86%
Dependency Graph
100%
LLM Behavioral Safety
100%

Behavioral Risk Signals

Network Access
1 finding
Filesystem Write
2 findings
Shell Execution
1 finding
Dynamic Code
2 findings
Excessive Permissions
1 finding

Security Findings2

SeverityFindingLayerLocation

Scan History

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