Slips is a modular behavioral-based Python intrusion prevention system that uses machine learning to detect malicious behaviors in the network traffic.
Slips was designed to focus on targeted attacks, detection of command and control channels to provide good visualisation for the analyst. Slips is able to analyze real live traffic and the large network captures in the type of a pcap files, Suricata, Zeek/Bro and Argus flows, and highlight suspicious behaviour and connections that needs to analyzed in depth.
How can you help?
All contributors are welcomed! Here are a few ideas and be sure to check our GitHub repository!
Run Slips and report bugs and needed features, and suggest ideas
Pull requests with a solved GitHub issue and new feature
Pull request with a new detection module.
Latest News
Our team is excited to share the latest news and features of Slips, our behavioral-based machine learning intrusion detection system.