Security Audit
firmao-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
firmao-automation received a trust score of 94/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Broad Dynamic Tool Execution and Programmatic Access.
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 | |
|---|---|---|---|---|
| MEDIUM | Broad Dynamic Tool Execution and Programmatic Access The skill leverages Rube MCP tools, specifically `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH`, which grant the LLM broad and dynamic control over Firmao operations. The instruction to 'Always call `RUBE_SEARCH_TOOLS` first to get current tool schemas' combined with `RUBE_MULTI_EXECUTE_TOOL` means the LLM can dynamically discover and execute any available Firmao functionality. Furthermore, `RUBE_REMOTE_WORKBENCH` is described as enabling 'Bulk ops' and allowing `run_composio_tool()`, suggesting a powerful programmatic execution environment for complex workflows. While these capabilities are central to an 'automation' skill, they represent a significant level of control over the integrated system. Users should be aware that enabling this skill effectively grants the LLM broad, dynamic control over their Firmao account, and any potential vulnerabilities in the Rube MCP or Firmao toolkit could be exploited through this interface. Ensure robust sandboxing and access controls are in place within the Rube MCP and the underlying Composio toolkits. Users should be explicitly informed about the extensive permissions granted to the LLM when enabling this skill, emphasizing the potential for broad data access and modification within their Firmao account. Consider implementing more granular permission scopes if possible, or requiring explicit user confirmation for high-impact operations. | LLM | SKILL.md:49 |
Scan History
Embed Code
[](https://skillshield.io/report/ec8117bb45b6823e)
Powered by SkillShield