fine-tuning-expert

Pass

Audited by Gen Agent Trust Hub on Aug 23, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill provides instructional content and code snippets for LLM fine-tuning using established industry-standard libraries such as transformers, peft, and vllm. All suggested practices align with secure machine learning development workflows.
  • [DATA_EXFILTRATION]: No hardcoded secrets or sensitive file path access were detected. The examples correctly demonstrate using environment variables or local server configurations for API clients.
  • [PROMPT_INJECTION]: While the skill is designed to process external training data, it includes robust mechanisms for data validation and quality filtering to prevent the ingestion of malicious or low-quality instructions.
  • [COMMAND_EXECUTION]: Shell command usage is confined to legitimate model conversion and deployment tasks, such as quantizing models with llama.cpp tools or starting vLLM inference servers.
Audit Metadata
Risk Level
SAFE
Analyzed
Aug 23, 2026, 07:57 AM
Security Audit — agent-trust-hub — fine-tuning-expert