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Security Audit

amygdala-memory

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
10
CRITICAL
Scanned 2 months ago
2
Critical
Immediate action required
2
High
Priority fixes suggested
11
Medium
Best practices review
1
Low
Acknowledged / Tracked

Trust Assessment

amygdala-memory 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 16 findings: 2 critical, 2 high, 11 medium, and 1 low severity. Key findings include Sensitive environment variable access: $HOME, jq command injection via --dimension argument, Path traversal via AGENT_ID environment variable.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 8/100, indicating areas for improvement.

Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
23%
Dependency Graph
100%
LLM Behavioral Safety
8%

Behavioral Risk Signals

Filesystem Write
2 findings
Shell Execution
15 findings
Dynamic Code
2 findings
Excessive Permissions
12 findings

Security Findings16

SeverityFindingLayerLocation

Scan History

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