Security Audit

byteforms-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

byteforms-automation received a trust score of 90/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.

SkillShield's automated analysis identified 2 findings: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Unclear security implications of RUBE_REMOTE_WORKBENCH, Broad access to Byteforms operations via RUBE_MULTI_EXECUTE_TOOL.

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 17, 2026 (commit 99e2a295). 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

2 findings

Excessive Permissions

2 findings

Security Findings2

Severity	Finding	Layer	Location
HIGH	Unclear security implications of RUBE_REMOTE_WORKBENCH The skill mentions `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' using `run_composio_tool()`. The term 'workbench' often implies a flexible execution environment, and 'bulk ops' suggests powerful, potentially unconstrained operations. Without detailed schema or documentation for `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`, the full scope of its capabilities and potential security implications (e.g., arbitrary code execution, broad data access) remains unclear. This could lead to excessive permissions if the tool is not properly sandboxed or if its capabilities are broader than intended for an LLM agent. Provide comprehensive documentation and schema for `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`, clearly outlining its capabilities, input parameters, and security boundaries. Ensure that its execution environment is securely sandboxed and that it does not permit arbitrary code execution or operations beyond its intended scope.	LLM	SKILL.md:71
INFO	Broad access to Byteforms operations via RUBE_MULTI_EXECUTE_TOOL The skill enables the LLM to discover and execute any available Byteforms operation through `RUBE_SEARCH_TOOLS` and `RUBE_MULTI_EXECUTE_TOOL`. This grants the LLM broad control over the connected Byteforms account, limited only by the permissions of the Byteforms connection established via `RUBE_MANAGE_CONNECTIONS`. Users should be aware of the full scope of actions the LLM can take on their behalf. Ensure users are fully informed about the scope of permissions granted to the LLM when using this skill and connecting their Byteforms account. Implement granular access controls within Byteforms or Rube MCP if possible to limit the LLM's capabilities to specific tasks.	LLM	SKILL.md:49

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