Security Audit
dreamstudio-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
dreamstudio-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'. If `run_composio_tool()` allows execution of arbitrary code or commands, a malicious user could craft prompts to inject and execute commands through this mechanism. The skill does not define the security boundaries or input validation of `run_composio_tool()`, making its usage a potential command injection risk. Clarify the capabilities and security implications of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Implement strict input validation and sandboxing for arguments passed to `run_composio_tool()` to prevent arbitrary command execution. If not intended for arbitrary execution, rename or restrict its functionality. | LLM | SKILL.md:39 |
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