model-optimization

Pass

Audited by Gen Agent Trust Hub on Feb 17, 2026

Risk Level: SAFE
Full Analysis
  • [General Security] (SAFE): Analysis of the skill body, scripts, and configurations revealed no malicious patterns. All code serves the primary purpose of model optimization using established frameworks.
  • [Indirect Prompt Injection] (SAFE): While the skill ingests training datasets which are technically untrusted external data, this is the standard and intended use-case for machine learning tools. No specific vulnerability surface for prompt injection or control-flow manipulation was found.
  • [Dynamic Execution] (SAFE): The script 'scripts/optuna_optimizer.py' uses dynamic instantiation of model classes via 'self.model_class(**params)'. This is a standard architectural pattern for optimization frameworks and does not involve unsafe string evaluation or execution of untrusted code.
  • [External Downloads] (SAFE): All referenced libraries (scikit-learn, PyTorch, Optuna, etc.) are reputable and standard in the data science ecosystem. No unverified or suspicious remote resources are accessed.
Audit Metadata
Risk Level
SAFE
Analyzed
Feb 17, 2026, 06:14 PM