Security Audit
sympla-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
sympla-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 Generic tool execution via RUBE_REMOTE_WORKBENCH allows broad 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 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 | Generic tool execution via RUBE_REMOTE_WORKBENCH allows broad access The skill documentation suggests using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. This construct allows the execution of arbitrary Composio tools. If the underlying Composio tools have broad permissions (e.g., filesystem access, network access to arbitrary domains, access to other sensitive APIs), this skill effectively grants the LLM access to those broad permissions without specific restrictions. An attacker could leverage this to instruct the LLM to execute a malicious Composio tool, potentially leading to unauthorized data access or system manipulation. Restrict the scope of `RUBE_REMOTE_WORKBENCH` to only allow specific, pre-approved Composio tools relevant to Sympla automation, or ensure that the Rube MCP environment enforces strict permission boundaries for tools executed via `run_composio_tool()`. Alternatively, provide more granular tools instead of a generic execution mechanism that can call any Composio tool. | LLM | SKILL.md:59 |
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