Security Audit

apiverve-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

apiverve-automation received a trust score of 80/100, 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 tool execution capabilities via Rube MCP, Unpinned dependency in manifest.

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

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Broad tool execution capabilities via Rube MCP The skill leverages `RUBE_SEARCH_TOOLS` to discover available tools and `RUBE_MULTI_EXECUTE_TOOL` to execute any discovered tool within the `apiverve` toolkit. Additionally, `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` suggests the ability to execute arbitrary Composio tools. This grants the skill very broad permissions to perform actions without granular control, potentially exceeding the principle of least privilege. An attacker who can manipulate the `tool_slug` or `arguments` could potentially execute unintended operations. Implement more granular access control for the Rube tools. If `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` are intended to be restricted, ensure the underlying Rube MCP system enforces these restrictions based on the skill's manifest or context. Explicitly list required tool slugs in the manifest if possible, rather than relying on dynamic discovery and execution of any tool.	LLM	SKILL.md:49
MEDIUM	Unpinned dependency in manifest The skill's manifest specifies a dependency on `rube` (`"mcp": ["rube"]`) without a version constraint. This means that any version of the `rube` dependency could be used, including future versions that might introduce vulnerabilities, breaking changes, or unexpected behavior. This increases the supply chain risk as the skill's behavior is not locked to a tested version of its dependency. Pin the `rube` dependency to a specific version or a version range (e.g., `"rube": "1.2.3"` or `"rube": "^1.0.0"`) in the manifest to ensure consistent and predictable behavior and to mitigate risks from unexpected updates.	LLM	SKILL.md

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