Description :

This project is a Flask-based web application designed to analyse and extract insights from cybersecurity data. It uses Retrieval-Augmented Generation (RAG) and the Llama 3.2 1B model to process the CISA Known Exploited Vulnerabilities (KEV) catalog and user-uploaded PDF documents. Developed as an undergraduate exchange project at the National Taipei University of Technology, the system specifically focuses on extracting and summarizing insights from CISA’s Known Exploited Vulnerabilities (KEV) catalog.