🐢 Open-Source Evaluation & Testing for AI & LLM systems
a prompt injection scanner for custom LLM applications
A security scanner for your LLM agentic workflows
RuLES: a benchmark for evaluating rule-following in language models
[CCS'24] SafeGen: Mitigating Unsafe Content Generation in Text-to-Image Models
Whistleblower is a offensive security tool for testing against system prompt leakage and capability discovery of an AI application exposed through API. Built for AI engineers, security researchers and folks who want to know what's going on inside the LLM-based app they use daily
The official implementation of the CCS'23 paper, Narcissus clean-label backdoor attack -- only takes THREE images to poison a face recognition dataset in a clean-label way and achieves a 99.89% attack success rate.
Framework for testing vulnerabilities of large language models (LLM).
Code for "Adversarial attack by dropping information." (ICCV 2021)
Train AI (Keras + Tensorflow) to defend apps with Django REST Framework + Celery + Swagger + JWT - deploys to Kubernetes and OpenShift Container Platform
ATLAS tactics, techniques, and case studies data
Performing website vulnerability scanning usi 10000 ng OpenAI technologie
Code scanner to check for issues in prompts and LLM calls
Unofficial pytorch implementation of paper: Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
[NDSS'24] Inaudible Adversarial Perturbation: Manipulating the Recognition of User Speech in Real Time
This repository provide the studies on the security of language models for code (CodeLMs).
pytorch implementation of Parametric Noise Injection for adversarial defense
[IJCAI 2024] Imperio is an LLM-powered backdoor attack. It allows the adversary to issue language-guided instructions to control the victim model's prediction for arbitrary targets.
Learning to Identify Critical States for Reinforcement Learning from Videos (Accepted to ICCV'23)
Python library for Modzy Machine Learning Operations (MLOps) Platform
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