Type : 1 person full time 350hrs (12 weeks)
Technology : python, bash, scikit-learn, pytorch, tensorflow, security, AI, LLMs
Mentor : Huzaifa Sidhpurwala
Email : huzaifas@redhat.com
Description This project aims to automatically parse, classify, and prioritize security-related logs on a Fedora system. The tool will aggregate logs from multiple sources (e.g., SELinux, systemd journal, audit logs) and apply basic machine learning (ML) or natural language processing (NLP) techniques to identify and prioritize potential security events. It will help administrators quickly spot critical alerts while reducing noise from routine messages.