adversarial-attacks
There are 911 repositories under adversarial-attacks topic.
BishopFox/sliver
Adversary Emulation Framework
Trusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
makcedward/nlpaug
Data augmentation for NLP
QData/TextAttack
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
microsoft/promptbench
A unified evaluation framework for large language models
Harry24k/adversarial-attacks-pytorch
PyTorch implementation of adversarial attacks [torchattacks]
thunlp/TAADpapers
Must-read Papers on Textual Adversarial Attack and Defense
advboxes/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.
BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research
DSE-MSU/DeepRobust
A pytorch adversarial library for attack and defense methods on images and graphs
shubhomoydas/ad_examples
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.
safe-graph/graph-adversarial-learning-literature
A curated list of adversarial attacks and defenses papers on graph-structured data.
ThuCCSLab/Awesome-LM-SSP
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
thunlp/OpenAttack
An Open-Source Package for Textual Adversarial Attack.
fra31/auto-attack
Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
hendrycks/natural-adv-examples
A Harder ImageNet Test Set (CVPR 2021)
MadryLab/photoguard
Raising the Cost of Malicious AI-Powered Image Editing
jind11/TextFooler
A Model for Natural Language Attack on Text Classification and Inference
thu-ml/ares
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
sarathknv/adversarial-examples-pytorch
Implementation of Papers on Adversarial Examples
ChandlerBang/awesome-graph-attack-papers
Adversarial attacks and defenses on Graph Neural Networks.
Koukyosyumei/AIJack
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
HuntDownProject/HEDnsExtractor
A suite for hunting suspicious targets, expose domains and phishing discovery
natanielruiz/disrupting-deepfakes
🔥🔥Defending Against Deepfakes Using Adversarial Attacks on Conditional Image Translation Networks
deadbits/vigil-llm
⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs
agencyenterprise/PromptInject
PromptInject is a framework that assembles prompts in a modular fashion to provide a quantitative analysis of the robustness of LLMs to adversarial prompt attacks. 🏆 Best Paper Awards @ NeurIPS ML Safety Workshop 2022
hbaniecki/adversarial-explainable-ai
💡 Adversarial attacks on explanations and how to defend them
ChandlerBang/Pro-GNN
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
ain-soph/trojanzoo
TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.
1Konny/FGSM
Simple pytorch implementation of FGSM and I-FGSM
automorphic-ai/aegis
Self-hardening firewall for large language models
pumpbin/pumpbin
🎃 PumpBin is an Implant Generation Platform.
kabkabm/defensegan
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)
danielzuegner/nettack
Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
haofanwang/Awesome-Computer-Vision
Awesome Resources for Advanced Computer Vision Topics