A simple packet sniffer written in Python, with the ability to utilize Wireshark dissectors (display filters.)

This project uses a Random Forest model trained on the NSL-KDD dataset to improve intrusion detection accuracy by categorizing network traffic as either normal or malicious. It features live packet capture and real-time predictions through a Flask web application, demonstrating the adaptability of machine learning in cybersecurity.