Security Audit

waiverfile-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

waiverfile-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 Potential Command Injection via RUBE_REMOTE_WORKBENCH.

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

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
HIGH	Potential Command Injection via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' with `run_composio_tool()`. The term 'workbench' often implies an environment capable of executing arbitrary code or complex operations. Without clear sandboxing or limitations defined for `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`, there is a significant risk of command injection. An attacker who can manipulate the inputs to this tool could potentially execute arbitrary commands on the underlying system, leading to data exfiltration, system compromise, or denial of service. This also implies excessive permissions (SS-LLM-005) if the tool's scope is not properly restricted. Clarify the exact capabilities and security boundaries of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows arbitrary code execution, it should be removed or heavily restricted. If it is intended for batching safe operations, this should be explicitly stated, and its inputs must be strictly validated and sanitized to prevent command injection. Implement robust sandboxing for any code execution environment.	LLM	SKILL.md:70

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