Security Audit

hookdeck-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

hookdeck-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 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Skill enables broad tool execution 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

85%

Behavioral Risk Signals

Shell Execution

1 finding

Dynamic Code

1 finding

Security Findings1

Severity	Finding	Layer	Location
HIGH	Skill enables broad tool execution via Rube MCP The skill leverages Rube MCP's `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` to perform Hookdeck operations. These tools allow for dynamic discovery and execution of a wide range of actions within the Hookdeck service. This grants the host LLM extensive capabilities, potentially leading to unintended or unauthorized actions if the LLM's prompts or internal reasoning are compromised, or if the Rube MCP itself is misconfigured. The skill documentation encourages dynamic tool discovery via `RUBE_SEARCH_TOOLS`, which further broadens the potential execution surface without explicit constraints defined within the skill itself. Implement strict guardrails and fine-grained access controls within the Rube MCP for the `hookdeck` toolkit. Ensure the host LLM's prompts are carefully designed to limit the scope of operations. Consider using a Rube MCP configuration that restricts the available tool slugs or arguments to only those absolutely necessary for the skill's intended purpose, rather than allowing full dynamic discovery and execution.	LLM	SKILL.md:46

Scan History

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