Security Audit

wachete-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

wachete-automation received a trust score of 83/100, 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 Command Injection and Excessive Permissions via RUBE_REMOTE_WORKBENCH, Direct Dependency on External 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 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

78%

Behavioral Risk Signals

Network Access

1 finding

Shell Execution

2 findings

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Potential Command Injection and Excessive Permissions via RUBE_REMOTE_WORKBENCH The skill recommends using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'workbench' and the function `run_composio_tool()` strongly suggest the capability to execute arbitrary code or commands within an environment. If the arguments to `run_composio_tool()` can be influenced by untrusted input, this presents a significant command injection vulnerability. Furthermore, a 'workbench' typically implies broad system access, leading to excessive permissions that could be exploited for data exfiltration or system compromise. Clarify the exact capabilities and security boundaries of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows arbitrary code execution, restrict its use or provide strong input validation and sandboxing. If not, rename to avoid implying such capabilities.	LLM	SKILL.md:78
MEDIUM	Direct Dependency on External MCP Introduces Supply Chain Risk The skill explicitly instructs users to add `https://rube.app/mcp` as an MCP server. This creates a direct dependency on an external, third-party service for the skill's core functionality. If `rube.app` were to be compromised, or if the service itself were to become malicious, it could lead to the execution of unauthorized tools, data exfiltration, or other security incidents through the `RUBE_` tools. This is a supply chain risk as the security posture of the skill is tied to an external entity. Implement robust vetting processes for third-party services. Consider providing clear warnings about the risks associated with connecting to external MCPs. Ensure the `rube.app` endpoint is secured and trusted.	LLM	SKILL.md:28

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