Popular GitHub Repositories for Offensive Security

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.

Opiniated RAG for integrating GenAI in your apps ? Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.

This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), artificial intelligence security, vulnerability research, exploit development, reverse engineering, and more.

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents

This is a collection of tutorials for learning how to use Docker with various tools. Contributions welcome.

:octocat: Machine Learning for Cyber Security

the LLM vulnerability scanner

An adversarial example library for constructing attacks, building defenses, and benchmarking both

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

? Open-Source Evaluation & Testing library for LLM Agents

HexStrike AI MCP Agents is an advanced MCP server that lets AI agents (Claude, GPT, Copilot, etc.) autonomously run 150+ cybersecurity tools for automated pentesting, vulnerability discovery, bug bounty automation, and security research. Seamlessly bridge LLMs with real-world offensive security capabilities.

? Open-Source Evaluation & Testing for AI & LLM systems

Python library for Modzy Machine Learning Operations (MLOps) Platform

a self-hosted solution for running ai-generated code in secure sandboxes

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

ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, Adversarial Machine Learning.

TextAttack ? is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

Connect any AI model to 600+ integrations; powered by MCP ? ?

The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.