Trust Assessment
folk-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 Arbitrary Code Execution 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 Arbitrary Code Execution via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'workbench' typically implies a general-purpose execution environment, and `run_composio_tool()` suggests the ability to execute arbitrary Composio tools. If this function allows for arbitrary code execution, shell command execution, or access to the underlying filesystem, it represents a significant command injection vulnerability (SS-LLM-003) and grants excessive permissions to the skill. A malicious prompt could leverage this to execute arbitrary commands on the host system or within the agent's environment, leading to data exfiltration or system compromise. Clarify the exact capabilities and sandboxing of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows arbitrary code/shell execution, ensure it runs in a highly restricted, isolated, and ephemeral environment with minimal permissions. Consider if such a powerful tool is strictly necessary for the skill's stated purpose. If not, remove or restrict its availability. | LLM | SKILL.md:68 |
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