Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

the LLM vulnerability scanner

NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.

🐢 Open-Source Evaluation & Testing library for LLM Agents

[CCS'24] A dataset consists of 15,140 ChatGPT prompts from Reddit, Discord, websites, and open-source datasets (including 1,405 jailbreak prompts).

The Security Toolkit for LLM Interactions

OWASP Top 10 for Large Language Model Apps (Part of the GenAI Security Project)

A.I.G (AI-Infra-Guard) is a comprehensive, intelligent, and easy-to-use AI Red Teaming platform developed by Tencent Zhuque Lab.

Agentic LLM Vulnerability Scanner / AI red teaming kit 🧪

A secure low code honeypot framework, leveraging AI for System Virtualization. 🇮🇹

A powerful tool for automated LLM fuzzing. It is designed to help developers and security researchers identify and mitigate potential jailbreaks in their LLM APIs.

A security scanner for your LLM agentic workflows

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

AspGoat is an intentionally vulnerable ASP.NET Core application for learning and practicing web application security.

⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs

This repository provides a benchmark for prompt injection attacks and defenses

Papers and resources related to the security and privacy of LLMs 🤖

🏴‍☠️ Hacking Guides, Demos and Proof-of-Concepts 🥷

Experimental tools to backdoor large language models by re-writing their system prompts at a raw parameter level. This allows you to potentially execute offline remote code execution without running any actual code on the victim's machine or thwart LLM-based fraud/moderation systems.

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