AdNauseam: Fight back against advertising surveillance

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

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.

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP

A Toolbox for Adversarial Robustness Research

🗣️ Tool to generate adversarial text examples and test machine learning models against them

Implementation of Papers on Adversarial Examples

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

A curated list of awesome resources for adversarial examples in deep learning

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)

DEEPSEC: A Uniform Platform for Security Analysis of Deep Learning Model

Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.

Physical adversarial attack for fooling the Faster R-CNN object detector

PyTorch library for adversarial attack and training

A PyTorch Toolbox for creating adversarial examples that fool neural networks.

Adversarial attacks and defenses on Graph Neural Networks.

Code for "Detecting Adversarial Samples from Artifacts" (Feinman et al., 2017)

Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

NIPS Adversarial Vision Challenge

Randomized Smoothing of All Shapes and Sizes (ICML 2020).

Adversarial Attacks on Deep Neural Networks for Time Series Classification

This is the implementation of MalConv proposed in [Malware Detection by Eating a Whole EXE](https://arxiv.org/abs/1710.09435) and its adversarial sample crafting.

对抗样本（Adversarial Examples）和投毒攻击（Poisoning Attacks）相关资料

Implemention of Fast Gradient Sign Method for generating adversarial examples in Keras

Take further steps in the arms race of adversarial examples with only preprocessing.