Security Audit
nango-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
nango-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 Broad execution capabilities via Rube MCP tools.
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
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Broad execution capabilities via Rube MCP tools The skill grants the AI agent broad capabilities to interact with and execute operations within the Nango ecosystem via Rube MCP. Specifically, `RUBE_MULTI_EXECUTE_TOOL` allows the agent to execute any discovered Nango tool with arbitrary, schema-compliant arguments. This means the agent can perform a wide range of actions on behalf of the user through connected Nango integrations. Furthermore, the mention of `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` suggests the ability to execute arbitrary Composio tools within a remote environment, which could imply significant control and potential for misuse, including data manipulation, deletion, or exfiltration. Review the necessity of granting such broad execution capabilities. Consider implementing stricter access controls, granular permissions for specific Nango operations, or requiring explicit user confirmation for sensitive actions. If `RUBE_REMOTE_WORKBENCH` allows arbitrary code execution, ensure it operates within a highly sandboxed and restricted environment, and clarify its exact capabilities and limitations to prevent unintended actions. | LLM | SKILL.md:57 |
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