LLM-QC/AdversariaLLM

LLM Adversarial Robustness Toolkit, a toolkit for evaluating LLM robustness through adversarial testing.

An easy-to-use Python framework to generate adversarial jailbreak prompts.

A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.

Toolkit for AI whitehats, internal red teams, llm bug bounty hunters and mlops - Adversarial testing for AI, LLMs, and Agents.

LLM security testing framework for detecting prompt injection, jailbreaks, and adversarial attacks — 190+ probes, 28 providers, single Go binary

This repository provides a benchmark for prompt injection attacks and defenses in LLMs

A structured, versioned archive of adversarial prompt engineering techniques against Large Language Models — for AI safety research, red-teaming, and defensive hardening.

Simple Prompt Injection Kit for Evaluation and Exploitation

the LLM vulnerability scanner