Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes
-
Updated
Aug 2, 2023 - Python
Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, Adversarial Machine Learning.
A Toolbox for Adversarial Robustness Research
The Security Toolkit for LLM Interactions
A curated list of useful resources that cover Offensive AI.
A curated list of adversarial attacks and defenses papers on graph-structured data.
RobustBench: a standardized adversarial robustness benchmark [NeurIPS 2021 Benchmarks and Datasets Track]
T2F: text to face generation using Deep Learning
Unofficial PyTorch implementation of the paper titled "Progressive growing of GANs for improved Quality, Stability, and Variation"
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.
Papers and resources related to the security and privacy of LLMs 🤖
Provable adversarial robustness at ImageNet scale
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
A curated list of trustworthy deep learning papers. Daily updating...
Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs
TransferAttack is a pytorch framework to boost the adversarial transferability for image classification.
Add a description, image, and links to the adversarial-machine-learning topic page so that developers can more easily learn about it.
To associate your repository with the adversarial-machine-learning topic, visit your repo's landing page and select "manage topics."