Security Audit

boloforms-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

boloforms-automation received a trust score of 84/100, 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 execution capability via RUBE_REMOTE_WORKBENCH, Unpinned `rube` 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

Dynamic Code

2 findings

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Broad execution capability via RUBE_REMOTE_WORKBENCH The skill documentation recommends using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'Workbench' and the ability to 'run_composio_tool()' suggest a broad execution capability that could allow an LLM, if prompted maliciously, to execute arbitrary Composio tools or operations beyond the intended scope of Boloforms automation. If `run_composio_tool()` is not properly sandboxed or allows arbitrary code execution through its arguments, this could lead to command injection or unauthorized access to system resources. Clarify the exact scope and sandboxing of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows arbitrary code execution, consider restricting its availability or providing strong warnings and input validation. Ensure that the underlying Composio tools executed via this mechanism are strictly scoped and do not allow access to sensitive system resources or arbitrary command execution.	LLM	SKILL.md:50
MEDIUM	Unpinned `rube` dependency in manifest The skill's manifest specifies a dependency on `rube` (`"mcp": ["rube"]`) without a version constraint. This means that any future updates to the `rube` package, including potentially breaking changes or malicious code injections, could be automatically incorporated without explicit review, posing a supply chain risk. Pin the `rube` dependency to a specific, known-good version (e.g., `"mcp": ["rube@1.2.3"]`) to ensure deterministic builds and prevent unexpected changes or malicious updates from being automatically pulled in. Regularly review and update pinned dependencies.	LLM	SKILL.md

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