torchforge-rl-training
Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. Use when you want clean RL abstractions, easy algorithm experimentation, or scalable training with Monarch and TorchTitan.
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Low-risk findings worth noting
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tessl review fix ./06-post-training/torchforge/SKILL.mdLow
Low-risk findings.
2 low severity findings. 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 in SKILL.md points to loading a training dataset “openai/gsm8k” (a public dataset) and streaming it at runtime, so outsider-authored natural-language samples can enter the agent’s LLM context through the training/generation loop.
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The troubleshooting guide includes an explicit runtime install command "git clone https://github.com/meta-pytorch/monarch" followed by "cd monarch && pip install -e .", which fetches remote code and executes it, and Monarch is listed as a required dependency—so this is a runtime external dependency that can execute remote code (https://github.com/meta-pytorch/monarch).
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Commit
773a529
- Audited
- Security analysis
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