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adversarial-robustness-toolbox

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

textattack

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

foolbox

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

adversarial-vision-challenge

NIPS Adversarial Vision Challenge

deeprobust

A pytorch adversarial library for attack and defense methods on images and graphs

auto-lirpa

auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs

advertorch

A Toolbox for Adversarial Robustness Research

torchattack

🛡 A curated list of adversarial attacks in PyTorch, with a focus on transferable black-box attacks.

groot-trees

[ICML 2021] A fast algorithm for fitting robust decision trees. http://proceedings.mlr.press/v139/vos21a.html

adaptive-neighbourhoods

Python API for generating adapted and unique neighbourhoods for searching for adversarial examples.

adv-lib

Library containing PyTorch implementations of various adversarial attacks and resources

adversary

Creates adversarial text examples for machine learning models

foolbox-native

Foolbox Native brings native performance to Foolbox

advhash

Adversarial collision attacks on perceptual hashing functions

advbox

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

customattack

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

famework

Framework for Adversarial Malware Evaluation.

moorkh

A Python toolbox to create adversarial examples that fool neural networks in PyTorch.