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16 search results found

Guardrail ⭐ 278

Build LLM apps safely and securely🛡️

Llm_rules ⭐ 172

RuLES: a benchmark for evaluating rule-following in language models

Narcissus ⭐ 61

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.

Train Ai With Django Swagger Jwt ⭐ 57

Train AI (Keras + Tensorflow) to defend apps with Django REST Framework + Celery + Swagger + JWT - deploys to Kubernetes and OpenShift Container Platform

Vulnscan ⭐ 34

Performing website vulnerability scanning using OpenAI technologie

Atlas Data ⭐ 26

ATLAS tactics, techniques, and case studies data

Sdk Python ⭐ 23

Python library for Modzy Machine Learning Operations (MLOps) Platform

Code for "Adversarial attack by dropping information." (ICCV 2021)

Cvpr_2019_pni ⭐ 18

pytorch implementation of Parametric Noise Injection for adversarial defense

Unofficial pytorch implementation of paper: Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures

Ratemyai ⭐ 12

Prompt Engineering Tool for AI Models with cli prompt or api usage

Videorlcs ⭐ 12

Learning to Identify Critical States for Reinforcement Learning from Videos (Accepted to ICCV'23)

Meta Sift ⭐ 11

The official implementation of USENIX Security'23 paper "Meta-Sift" -- Ten minutes or less to find a 1000-size or larger clean subset on poisoned dataset.

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.

Antinex Client ⭐ 5

AntiNex python client for training and using pre-trained deep neural networks with JWT authentication

Attacking Distance Aware Attack ⭐ 5

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