fine-tuning-with-trl
Pass
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSINDIRECT_PROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill provides instructions to install the
trl,transformers,datasets,peft, andacceleratepackages from official registries. It also includes examples that fetch datasets and model weights from Hugging Face's official repository (e.g.,trl-lib/Capybara,Qwen/Qwen2.5-0.5B). These are well-known services and the downloads are standard for the described ML workflows.- [INDIRECT_PROMPT_INJECTION]: The skill facilitates the ingestion of external data for model training purposes, creating a surface for indirect prompt injection. Malicious instructions embedded in processed datasets could potentially influence the training process or the resulting model behavior. - Ingestion points: Code examples in
SKILL.md(lines 72, 105, 233),references/reward-modeling.md(line 21), andreferences/sft-training.md(line 49) demonstrate importing data from external sources usingload_dataset(). - Boundary markers: The documentation does not implement or recommend the use of delimiters or 'ignore embedded instructions' markers for processing external data.
- Capability inventory: The training scripts involve filesystem write capabilities through
trainer.save_model()and subprocess execution via library-specific CLI tools. - Sanitization: No sanitization, validation, or filtering of the ingested dataset content is included in the documentation examples.
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