Open Source Adversarial ML Tools
think TensorFlow Playground, but for Adversarial Examples! A visualization tool designed for learning and teaching - the attack library is limited in size, but it has a nice front-end to it with buttons you can press!
License: Apache License 2.0
library for adversarial attacks / defenses specifically for PyTorch.
License: GNU Lesser General Public License v3.0
library for testing adversarial attacks / defenses maintained by some of the most important names in adversarial ML, namely Ian Goodfellow (ex-Google Brain, now Apple) and Nicolas Papernot (Google Brain). Comes with some nice tutorials!
License: MIT License
Counterfit is a command-line tool and generic automation layer for assessing the security of machine learning systems.
License: MIT License
second biggest adversarial library. Has an even longer list of attacks - but no defenses or evaluation metrics. Geared more towards computer vision. Code easier to understand / modify than ART - also better for exploring blackbox attacks on surrogate models.
License: MIT License
ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
License: MIT License
Library and experiments for attacking machine learning in discrete domains using graph search.
License: MIT License
Last Updated: Dec 26, 2023