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

Data augmentation for NLP

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

Must-read Papers on Textual Adversarial Attack and Defense

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A Harder ImageNet Test Set

Implementation of Papers on Adversarial Examples

A Model for Natural Language Attack on Text Classification and Inference

A curated list of adversarial attacks and defenses papers on graph-structured data.

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

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

Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

A pytorch implementations of Adversarial attacks and utils

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

Implementation for <Decoupled Networks> in CVPR'18.

Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"

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

🔥🔥Defending Against Deepfakes Using Adversarial Attacks on Conditional Image Translation Networks

Simple pytorch implementation of FGSM and I-FGSM

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

Adversarial attacks and defenses on Graph Neural Networks.

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

scratchai is a Deep Learning library that aims to store all Deep Learning algorithms. With easy calls to do all the common tasks in AI.

Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".

A list of awesome resources for adversarial attack and defense method in deep learning

Generative Adversarial Perturbations (CVPR 2018)

💀 A collection of methods to fool the deep neural network 💀