Security Audit

fullenrich-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

fullenrich-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 1 low severity. Key findings include Broad tool execution via RUBE_REMOTE_WORKBENCH, Unpinned Rube MCP dependency.

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

83%

Behavioral Risk Signals

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Broad tool execution via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. If `run_composio_tool()` allows execution of arbitrary Composio tools or scripts without fine-grained access control, it could grant excessive permissions to the LLM. This broad capability could be exploited if the LLM's input is compromised, leading to unintended or malicious actions beyond the intended scope of the Fullenrich skill. Implement strict access controls and sandboxing for `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure that the LLM can only invoke specific, pre-approved functions with limited parameters, or that the workbench environment is heavily restricted. Consider providing more granular tools instead of a generic 'run tool' mechanism if possible.	LLM	SKILL.md:70
LOW	Unpinned Rube MCP dependency The skill's manifest specifies a dependency on the `rube` MCP without a specific version. This means the skill will use whatever version of `rube` is currently available, which could lead to unexpected behavior, breaking changes, or the introduction of security vulnerabilities if the MCP updates in an incompatible or insecure way. If possible within the Composio ecosystem, specify a minimum or exact version for the `rube` MCP dependency in the manifest to ensure stability and security.	LLM	SKILL.md:1

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