Security Audit
neutrino-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
neutrino-automation received a trust score of 86/100, 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 Excessive Permissions 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 17, 2026 (commit 99e2a295). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Excessive Permissions via RUBE_REMOTE_WORKBENCH The skill enables access to `RUBE_REMOTE_WORKBENCH` which is described as allowing 'Bulk ops' and `run_composio_tool()`. This grants the LLM agent broad capabilities to execute arbitrary Composio tools, potentially in bulk, without specific constraints defined within this skill's documentation. If an agent is compromised or misused, this broad access could lead to significant unauthorized actions, data manipulation, or exfiltration depending on the scope of `composio_tool()` capabilities. Review the necessity of exposing `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` directly to the LLM agent. If broad bulk operations are required, consider implementing stricter guardrails, fine-grained access controls, or requiring explicit human approval for such powerful operations. Ensure the underlying `run_composio_tool()` has appropriate security measures and logging. | LLM | SKILL.md:70 |
Scan History
Embed Code
[](https://skillshield.io/report/2418b17819efe554)
Powered by SkillShield