Security Audit
mopinion-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
mopinion-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 Potential Command Injection 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
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Potential Command Injection via RUBE_REMOTE_WORKBENCH The skill instructs the LLM to use `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The naming convention ('Remote Workbench', 'run_composio_tool') strongly suggests that this tool provides an environment for executing arbitrary code or commands. If `run_composio_tool()` allows unconstrained execution, an attacker could craft a prompt to the LLM that leads to the execution of malicious commands via this tool. Investigate the implementation of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()` to confirm if arbitrary code execution is possible. If so, restrict its capabilities, implement strict input validation, or remove the tool if its functionality poses an unacceptable risk. Ensure the LLM's access to such powerful execution tools is carefully controlled and monitored. | LLM | SKILL.md:71 |
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