A secure low code deception runtime framework, leveraging AI for System Virtualization.

An open specification for agentic AI security evaluation and testing, from Cisco.

AI Security Platform: Defense (61 Rust engines + Micro-Model Swarm) + Offense (39K+ payloads)

AI/ML and Generative AI Security Assessment Framework for AWS. Automatically audit Amazon Bedrock and SageMaker & AgentCore workloads for security best practices

Agentic AI Security Bootcamp is a hands-on, research-driven training environment for analysing, attacking, and securing autonomous AI systems. The repository provides structured labs, adversarial evaluation frameworks, and red-teaming exercises covering multi-agent observability, prompt injection..

💰 Exocomp Agentic Environment for Go

Security working agreements for AI coding agents: hardened AGENTS.md, prompt/tool-injection guardrails, dependency hygiene, Scorecard-ready OSS setup

The dashcam and emergency brake for AI agents. A security proxy that physically blocks rogue LLM commands and generates cryptographically proven audit trails for enterprise compliance.

🤖 Test and secure AI systems with advanced techniques for Large Language Models, including jailbreaks and automated vulnerability scanners.

MLSecOps Practical Reference Guide, open-source AI and ML security handbook.

The open standard for AI agent integrity. Evaluate, enforce, and prove that autonomous agents are adversarially coherent, environmentally portable, and verifiably assured.

Open-source registry layer for auditable AI agent systems.

TypeScript/JavaScript SDK for AI Agent Security - Drop-in security for LangChain, CrewAI, AutoGPT and custom agents

A one stop resource to keep yourself updated for Agentic AI security with concepts, tools, frameworks, research, books, videos, courses etc.

Formal safety framework for AI agents. Pluggable LLM reasoning constrained by mathematically proven budget, invariant, and termination guarantee. 7 theorems enforced by construction, not by prompting. Includes Bayesian belief tracking, causal dependency graphs, sandboxed attestors, environment reconciliation, and a 155-test adversarial suite.

Essays on agentic AI security, decision-rights, reversibility-graded authority, manifest-declared action class, deterministic gates, and standards contribution method.

BioOS Cyber Genesis Challenge: An interactive web sandbox proving the 100% security paradigm of the Causal Operating System. Experience "Digital Causal Closure" firsthand: a world where hacking is a mathematical impossibility. Includes a vulnerable app protected by Z3 formal logic and hardware-validated intent (IRQ). Unhackable by design.

Website for the AVE open standard — the behavioral vulnerability classification standard for Agentic AI components.

Zero-trust security layer for Autonomous AI Agents. Proxy and block malicious LLM tool executions in real-time with Semantic DLP, RBAC, and Human-in-the-Loop.

Kill Switch Protocol for AI Agents and Healthcare Digital Twins.