ubc-provenance/PIDSMaker
A framework for building provenance-based intrusion detection systems with neural networks
This tool helps cybersecurity researchers and advanced security engineers develop and test new intrusion detection systems. It takes in detailed system activity records (provenance data) from various operating systems and security incidents. The output is a highly customizable intrusion detection system built with deep learning, capable of identifying advanced persistent threats. It's designed for those who need to experiment with and benchmark cutting-edge threat detection methods.
Use this if you are a cybersecurity researcher or a deep learning engineer focused on building, customizing, and evaluating provenance-based intrusion detection systems against known threat datasets.
Not ideal if you are an IT administrator or security analyst looking for an out-of-the-box intrusion detection system to deploy in a production environment without significant research and development.
Stars
81
Forks
28
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 06, 2026
Commits (30d)
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