Security Audit
crowdin-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
crowdin-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 Broad tool 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 | Broad tool execution via RUBE_REMOTE_WORKBENCH The skill documentation mentions `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. This suggests the ability to execute arbitrary Composio tools, potentially extending the skill's capabilities beyond Crowdin-specific operations. If `run_composio_tool()` can invoke any Composio tool, it grants the skill access to a much broader set of functionalities and potentially sensitive systems than implied by its 'crowdin-automation' name. This could lead to unintended actions or privilege escalation if the underlying Composio tools have broad permissions. Clarify the scope of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows execution of any Composio tool, consider restricting its capabilities for this specific skill to only Crowdin-related tools, or explicitly document the broader permissions and their implications. Implement strict access controls and sandboxing for `RUBE_REMOTE_WORKBENCH` to prevent unintended access to non-Crowdin functionalities. | LLM | SKILL.md:80 |
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