Security Audit

worksnaps-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

worksnaps-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, 0 high, 1 medium, and 0 low severity. Key findings include Broad Execution Capability 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

93%

Behavioral Risk Signals

Network Access

1 finding

Filesystem Write

1 finding

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Broad Execution Capability via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' using `run_composio_tool()`. This suggests a powerful, potentially unconstrained execution environment. If `run_composio_tool()` allows arbitrary code execution, shell commands, or broad file system/network access beyond the intended Worksnaps API, it represents an excessive permission. An attacker could potentially leverage this tool to execute malicious commands, access sensitive data, or interact with unintended external systems. The documentation lacks specifics on the sandboxing or limitations of this 'workbench' environment. Provide clear documentation on the security boundaries and capabilities of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure that this tool operates within a strictly sandboxed environment, adheres to the principle of least privilege, and prevents arbitrary code execution or access to host system resources. Implement robust input validation and authorization checks for any operations performed via the workbench.	LLM	SKILL.md:70

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