Security Audit

eversign-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 27904475d127

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

eversign-automation received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via RUBE_REMOTE_WORKBENCH.

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 27904475). 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

85%

Behavioral Risk Signals

Shell Execution

1 finding

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
HIGH	Potential Command Injection via RUBE_REMOTE_WORKBENCH The skill's 'Quick Reference' section recommends using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'workbench' and 'run_composio_tool()' strongly suggest capabilities for executing code or commands. If the inputs to `RUBE_REMOTE_WORKBENCH` or `run_composio_tool()` are not rigorously validated and sanitized, this could allow a malicious actor to inject and execute arbitrary commands, leading to command injection and potentially excessive permissions on the underlying system. The skill description provides no warnings or guidance on how to securely use this powerful tool. Add explicit warnings and detailed guidance on the secure use of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Clearly document its capabilities, potential risks, and any required input validation or sandboxing mechanisms. If arbitrary code execution is possible, this should be highlighted, and strong security controls must be in place and communicated.	LLM	SKILL.md:80

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