Security Audit

bookingmood-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

bookingmood-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 2 findings: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Excessive Permissions/Command Injection via RUBE_REMOTE_WORKBENCH, Reliance on External Rube MCP for Core Functionality.

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

Network Access

1 finding

Shell Execution

2 findings

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Potential Excessive Permissions/Command Injection via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. If `run_composio_tool()` allows the execution of arbitrary commands, scripts, or unconstrained access to system resources within the 'workbench' environment, it could lead to command injection or excessive permissions. An attacker could potentially craft inputs to execute malicious code or access sensitive data through this mechanism. The documentation does not specify the sandboxing or limitations of this function. Clarify the exact capabilities and security boundaries of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure it operates within a strictly sandboxed environment and only allows execution of explicitly whitelisted and safe operations. Provide examples of its safe usage and limitations, and detail any security controls in place.	LLM	SKILL.md:73
INFO	Reliance on External Rube MCP for Core Functionality The skill explicitly requires and relies on the Rube MCP (`https://rube.app/mcp`) for all its core functionality, including tool discovery, connection management, and execution. While not a direct vulnerability in the skill's code, this introduces a dependency on an external service. A compromise of the Rube MCP infrastructure or its API could potentially impact the security, integrity, and availability of operations performed by this skill. Ensure the Rube MCP provider follows robust security practices and has a strong security posture. Consider implementing monitoring for unusual activity or changes in the MCP's behavior. Document the security implications and risk mitigation strategies associated with relying on external Managed Control Planes.	LLM	SKILL.md:20

Scan History

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