Adversarial & Red-teaming Tools

Python Risk Identification Tool for generative AI. Microsoft's open-source framework for automated red teaming with multi-modal attack support, crescendo strategies, and 100+ operations experience. MIT licensed.

Open-source system for automatic censorship and robustness suppression removal in language-model outputs.

Agentic LLM vulnerability scanner and AI red teaming kit with multi-step attack simulation and automated security probing. Apache 2.0 licensed.

Programmable guardrails toolkit for LLM-based conversational systems. Uses Colang DSL to define safety rules, dialog flows, and content boundaries. Integrates with LangChain, LangGraph, and LlamaIndex for production deployments. Apache 2.0 licensed.

Input/output validation framework for building reliable AI applications. Detects and mitigates risks through composable validators for PII, toxicity, prompt injection, and structured output validation. Features Guardrails Hub with 50+ pre-built validators. Apache 2.0 licensed.

Trained models and code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using PyTorch Lightning and Transformers for toxicity, severe toxicity, obscene, threat, insult, identity attack, and sexual explicit content detection. Apache 2.0 licensed.

AI-powered agentic red team framework that automates offensive security operations from reconnaissance to exploitation to post-exploitation with zero human intervention. Integrates multiple security tools for comprehensive penetration testing. MIT licensed.

Cybersecurity AI framework for semi- and fully-automating offensive and defensive security tasks. Purpose-built for cybersecurity use cases with agent-based architecture for vulnerability assessment and security operations. MIT licensed.

Full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation. Apache 2.0 licensed.

AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows. MIT licensed.

Protects AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers. MIT licensed.

Portable sandbox execution environment for AI agents with constrained filesystem and network boundaries, designed to reduce blast radius in tool-use and LLM autonomy tests.

An open-source schema intelligence and safety layer (like Cloudflare) between AI agents and databases. Exposes a read-only Model Context Protocol (MCP) interface with PII masking, structured query recovery, and tamper-evident SHA-256 audit logs. Apache 2.0 licensed.

Structured library of 754 cybersecurity skills mapped to five frameworks including MITRE ATT&CK and NIST CSF 2.0, compatible with Claude Code, Cursor, and agentskills.io. Apache 2.0 licensed.

Autonomous AI-powered penetration testing agent that identifies vulnerabilities and validates them with proof-of-concept exploits. Apache 2.0 licensed.