CleverHans is a Python library with the main purpose of providing good reference implementations of attacks for benchmarking machine learning models against adversarial examples. The main maintainers of this library are Ian Goodfellow and Nicolas Papernot. Attacks (i.e. methods for generating adversarial examples) are listed under /cleverhans and each of the supported frameworks has its own folder with attack implementations. CleverHans also aims to implement a set of defenses, but this is currently work in progress (currently there is only a defense implementation for PyTorch). Read more...

Foolbox is a comprehensive adversarial library for attacking machine learning models, with a focus on neural networks in computer vision. At the moment of writing FoolBox contains 41 gradient-based and decision-based adversarial attacks, making it the second biggest adversial library after ART . A notable difference with ART is that Foolbox only contains attacks, but no defenses and evaluation metrics. The library is very user-friendly, with a clear API and documentation. Read more...