Security Audit

userlist-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

userlist-automation received a trust score of 82/100, 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 Broad execution capability via RUBE_REMOTE_WORKBENCH, Unpinned dependency on Rube MCP.

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	Broad execution capability via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'workbench' and the generic `run_composio_tool()` suggest a capability to execute arbitrary Composio tools or even custom code within a remote environment. Without strict sandboxing or explicit scope limitations, this could allow the LLM to execute operations beyond the intended Userlist domain, potentially leading to data manipulation, unauthorized access, or command injection if `run_composio_tool()` is not sufficiently restricted. Restrict the capabilities of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()` to only Userlist-specific operations. Ensure strong sandboxing and input validation for any code executed via this mechanism. Clearly document the scope and limitations of `run_composio_tool()`.	LLM	SKILL.md:79
MEDIUM	Unpinned dependency on Rube MCP The skill manifest declares a dependency on `mcp: ["rube"]` and refers to `https://rube.app/mcp`. There is no version pinning or integrity check (e.g., hash) specified for the Rube MCP dependency. This exposes the skill to supply chain risks, as a compromise of the `rube.app` endpoint or the Rube MCP itself could lead to the skill loading and executing malicious code without detection. Implement version pinning for the `rube` MCP dependency (e.g., `mcp: ["rube@1.2.3"]`) and consider adding integrity checks (e.g., hashes) if the platform supports it, to ensure that only trusted versions of the dependency are loaded.	LLM	SKILL.md:1

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