quantizing-models-bitsandbytes

Pass

Audited by Gen Agent Trust Hub on Sep 9, 2026

Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
  • [INDIRECT_PROMPT_INJECTION]: The skill describes workflows for fine-tuning models on external datasets, creating a surface where malicious instructions embedded in the data could potentially influence the agent's behavior during training or evaluation.\n
  • Ingestion points: Loading datasets from external sources (e.g., HuggingFace Datasets) in references/qlora-training.md.\n
  • Boundary markers: The provided code snippets do not include explicit delimiters or instructions to ignore potential commands within the dataset content.\n
  • Capability inventory: The workflows include file system write operations (save_pretrained, output_dir) and the use of the accelerate launch command for distributed training.\n
  • Sanitization: The instructions do not specify validation or sanitization steps for the ingested dataset content.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 9, 2026, 07:06 PM
Security Audit — agent-trust-hub — quantizing-models-bitsandbytes