MJ8753/cyber-quntum — reverse-engineered prompt

Build me a beginner friendly cybersecurity attack detection project in Python.

I want it to train on a cybersecurity attacks CSV, detect suspicious network events, and show the results in a simple Streamlit dashboard. It should save model outputs like feature importance and results, and it should be able to run from the command line.

Please also add a quantum anomaly detection module using IBM Quantum. It should work in two modes, local simulator by default and real IBM Quantum hardware if I provide an API key. For each event, create a simple quantum circuit from fields like ports, packet length, protocol, anomaly score, alerts, severity, and malware indicators. Then combine the quantum score with a normal classical score and return a final decision like anomaly detected and recommended action.

Include a small FastAPI or Flask endpoint for posting one cybersecurity event as JSON, plus good error handling for missing fields, bad API keys, network failures, and missing model files. Save every quantum run as a JSON file. Look up current IBM Quantum docs online if needed.