verl-rl-training
Pass
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: SAFE
Full Analysis
- [SAFE] (SAFE): The content consists entirely of technical documentation and configuration examples. No malicious code, obfuscation, or injection attempts were detected.
- [EXTERNAL_DOWNLOADS] (LOW): The documentation recommends installing the 'vllm' package via pip and references the official 'volcengine/verl' GitHub repository. These are standard practices for using the library and do not represent a security risk in this context.
- [COMMAND_EXECUTION] (LOW): Provides standard shell commands for Ray cluster management, environment variable configuration (e.g., NCCL, CUDA), and data verification. These are routine administrative tasks for distributed machine learning environments.
- [DYNAMIC_EXECUTION] (LOW): The framework supports loading custom reward functions from local Python files via configuration. While this involves dynamic code loading, it is a primary feature of the reinforcement learning framework being documented and is restricted to local paths provided by the user.
Audit Metadata