Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
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Updated
Jul 18, 2024 - Python
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
🐢 Open-Source Evaluation & Testing for LLMs and ML models
The open-sourced Python toolbox for backdoor attacks and defenses.
Deliver safe & effective language models
[ICML 2024] TrustLLM: Trustworthiness in Large Language Models
A toolkit for tools and techniques related to the privacy and compliance of AI models.
🚀 A fast safe reinforcement learning library in PyTorch
Moonshot - A simple and modular tool to evaluate and red-team any LLM application.
A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.
[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory
Framework for Adversarial Malware Evaluation.
[TPAMI, 2023] Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
[ACM MM22] Towards Robust Video Object Segmentation with Adaptive Object Calibration, ACM Multimedia 2022
SyReNN: Symbolic Representations for Neural Networks
[NeurIPS-2023] Annual Conference on Neural Information Processing Systems
MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs.
[USENIX Security 2025] PoisonedRAG: Knowledge Poisoning Attacks to Retrieval-Augmented Generation of Large Language Models
Code from PLDI '21 paper "Provable Repair of Deep Neural Networks."
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