Skip to main content

Security Audit

fathom

github.com/openclaw/skills
AI SkillCommit 13146e6a3d46
65
CAUTION
Scanned 2 months ago
5
Critical
Immediate action required
1
High
Priority fixes suggested
0
Medium
Best practices review
0
Low
Acknowledged / Tracked

Trust Assessment

fathom received a trust score of 65/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 6 findings: 5 critical, 1 high, 0 medium, and 0 low severity. Key findings include Command Injection via Recording ID in get-summary.sh, Command Injection via Recording ID in get-transcript.sh, Command Injection via URL parameters in list-calls.sh.

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

Behavioral Risk Signals

Network Access
6 findings
Shell Execution
5 findings
Dynamic Code
5 findings

Security Findings6

SeverityFindingLayerLocation

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/a87dbb61e0cd1f60.svg)](https://skillshield.io/report/a87dbb61e0cd1f60)
SkillShield Badge

Powered by SkillShield