Security Audit

faceup-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

faceup-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 Unpinned External MCP Dependency, Broad Tool Execution Capabilities via 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

2 findings

Filesystem Write

1 finding

Shell Execution

1 finding

Dynamic Code

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Broad Tool Execution Capabilities via Rube MCP The skill is designed to dynamically discover and execute tools via `RUBE_SEARCH_TOOLS` and `RUBE_MULTI_EXECUTE_TOOL`, and also exposes `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()`. This grants the skill the ability to invoke any tool available through the Rube MCP for Faceup, and potentially other Composio tools. If these underlying tools possess broad system access (e.g., file system, network, arbitrary code execution) or handle sensitive data without strict scope limitations, the skill inherits these excessive permissions. The `RUBE_REMOTE_WORKBENCH` is particularly concerning as it implies a general remote execution environment, which could be exploited for command injection if not properly sandboxed and restricted. Implement strict access controls and scope limitations for the tools accessible via `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH`. Ensure that the underlying Rube MCP and Composio tools are sandboxed and that `run_composio_tool()` is restricted to a predefined, minimal set of safe operations. Clearly document the exact permissions and potential impact of each accessible tool.	LLM	SKILL.md:47
MEDIUM	Unpinned External MCP Dependency The skill relies on an external Managed Control Plane (MCP) at `https://rube.app/mcp` without specifying a version or pinning mechanism. This introduces a supply chain risk, as changes to the remote MCP service could introduce breaking changes or malicious behavior without explicit user consent or update to the skill. Implement version pinning or content-based integrity checks for external MCP dependencies to ensure consistent and secure behavior. Consider hosting critical dependencies locally or through trusted, version-controlled registries.	LLM	SKILL.md:20

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