Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
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Updated
Jul 2, 2024 - Python
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
The Security Toolkit for LLM Interactions
Papers and resources related to the security and privacy of LLMs 🤖
RobustBench: a standardized adversarial robustness benchmark [NeurIPS'21 Benchmarks and Datasets Track]
Machine Learning Security Library
Official implementation of paper: DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers
The fastest && easiest LLM security and privacy guardrails for GenAI apps.
TransferAttack is a pytorch framework to boost the adversarial transferability for image classification.
GAN-GRID: A Novel Adversarial Attack on Smart Grid Stability Prediction
A curated list of useful resources that cover Offensive AI.
ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, Adversarial Machine Learning.
Awesome-ML-Supply-Chain-Security-Papers
A curated list of trustworthy deep learning papers. Daily updating...
Implementing various Generative Adversarial Networks
Reading list for adversarial perspective and robustness in deep reinforcement learning.
Official implementation of "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models"
Official Source Code of the paper "Exploring Effective Data for Surrogate Training Towards Black-box Attack", which is accepted by CVPR 2022
[CVPR2024 Highlight] Strong Transferable Adversarial Attacks via Ensembled Asymptotically Normal Distribution Learning
Solution for the Trojan Detection Challenge (TDC2022 - https://trojandetection.ai) as part of NeurIPS 2022
Keras with Tensorflow implementation of our paper "Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces" which is published in IEEE Transactions on Information Forensics and Security (TIFS).
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