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Security Audit

cellcog

github.com/CellCog/cellcog_python
AI SkillCommit 89ffa28e56d9
78
TRUSTED
Scanned about 2 months ago
0
Critical
Immediate action required
1
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

cellcog received a trust score of 78/100, 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, 1 high, 1 medium, and 0 low severity. Key findings include Potential Data Exfiltration via Arbitrary File Access, Unpinned Dependency in Installation Instructions.

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 20, 2026 (commit 89ffa28e). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis
100%
Static Code Analysis
78%
Dependency Graph
100%
LLM Behavioral Safety
100%

Behavioral Risk Signals

Filesystem Write
1 finding
Shell Execution
2 findings
Excessive Permissions
1 finding

Security Findings2

SeverityFindingLayerLocation

Scan History

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