Security Audit
openperplex-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
openperplex-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, 0 high, 1 medium, and 0 low severity. Key findings include Broad tool execution capability 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 | |
|---|---|---|---|---|
| MEDIUM | Broad tool execution capability via RUBE_REMOTE_WORKBENCH The skill documentation for 'openperplex-automation' describes the use of `RUBE_REMOTE_WORKBENCH` for 'Bulk ops', which includes the ability to call `run_composio_tool()`. This function appears to allow the execution of arbitrary Composio tools, potentially extending beyond the intended scope of Openperplex automation. If the LLM is not carefully constrained, this broad capability could lead to the execution of tools with excessive permissions or unintended side effects across the broader Composio ecosystem. Restrict the `RUBE_REMOTE_WORKBENCH` tool's capabilities within this skill to only allow execution of Openperplex-specific tools. Alternatively, provide explicit and strict guidance to the LLM to only use this tool for Openperplex-related tasks, and ensure the underlying execution environment for `RUBE_REMOTE_WORKBENCH` is strictly sandboxed and monitored to prevent unintended actions. | LLM | SKILL.md:68 |
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