Security Audit

taggun-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned 6 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

taggun-automation received a trust score of 98/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.

SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 0 medium, and 1 low severity. Key findings include Reliance on external Rube MCP introduces supply chain 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 17, 2026 (commit 99e2a295). 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

98%

Behavioral Risk Signals

Network Access

1 finding

Security Findings1

Severity	Finding	Layer	Location
LOW	Reliance on external Rube MCP introduces supply chain risk The skill's functionality is entirely dependent on the Rube MCP service, hosted at `https://rube.app/mcp`. If this external service were to be compromised or become malicious, it could potentially serve harmful tool definitions or facilitate unintended actions through the `RUBE_*` tools. This represents a supply chain risk inherent in integrating with third-party services. Users should verify the trustworthiness of the `rube.app` domain and the Rube MCP service. Implement robust monitoring for any unusual activity or unauthorized tool usage. Consider security audits of third-party dependencies.	LLM	SKILL.md:17

Scan History

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