verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
67
83%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow involves loading user-specified training data files (e.g., `data.train_files` / Parquet containing `prompt` text) which becomes runtime LLM-readable input; this dataset is outsider-authored if it’s not provided by the operating user.
- Repository
- synthetic-sciences/openscience
- Commit
5f2a37b
- Audited
- Security analysis
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