ml-hyperparameter-tuning

This module is primarily distributed ML tuning/orchestration code (Ray Tune + Optuna-backed PostgreSQL + example CMA-ES and DARTS-like forward logic). It does not show overt malicious behavior (no exec/subprocess/backdoor/exfiltration logic). However, it contains a high-impact operational security flaw: plaintext hardcoded PostgreSQL credentials in the Optuna connection URL, plus fixed remote artifact storage to S3. Because the actual training_function/objective implementations are external, the strongest supply-chain risk to evaluate further is the behavior of those callables during trial execution, alongside strict access controls for the PostgreSQL and S3 endpoints.