Develop & Train Anomaly Detection Model

Based on the structured data extracted by `Marvin` (and augmented by `GPT-5` if chosen), develop and train an anomaly detection model. Select an appropriate unsupervised or semi-supervised algorithm suitable for detecting subtle, stealthy threats. Detail your feature engineering process, model architecture, training methodology, and how you evaluate its performance (e.g., using precision, recall, F1-score on a simulated dataset with known anomalies). Integrate this model into your Airflow pipeline.