agentic-ai-security

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

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

Open-source AI security lab: EN/RU academy, public Rust defenses, research and local input evaluation. Explore Spectorn for live protection.

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

Static analysis and attack-surface scanner for AI agents — SAST for prompts, tools, MCP servers, and agent workflows. Detects capabilities, prompt risks, tool permissions, and governance gaps before deployment.

💰 Exocomp Agentic Environment

Agentic AI security bootcamp: labs for multi-agent observability, prompt injection, LPCI, red-teaming, adversarial evaluation — hands-on training.

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

Kernel-enforced authority and runtime security for AI agents, autonomous systems, and general Linux workloads.

Claude code skills, agents, memory, profiles to accomplish cybersecurity tasks, projects, jobs with ease. claude-code, claude-plugin, claude-code-plugin, marketplace, security, genai-security.

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

Open-source context intelligence engine for AI coding agents — repository graph, precise code navigation, MCP, impact analysis, memory, and guarded edits.

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

Practitioner-led AI security control framework: 57 controls across 12 NIST AI 600-1 GenAI risk domains, mapped to MITRE ATLAS, in three tiers. Vendor-agnostic, CC BY 4.0.

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

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

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.

Risk-Aware Introspective RAG (RAI-RAG) is a safety-aligned RAG framework integrating introspective reasoning, risk-aware retrieval gating, and secure evidence filtering to build trustworthy, robust, and secure LLM and agentic AI systems.

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

Open admission layer for LLM agent harnesses: forbidden-path quarantine + cross-iteration escalation monitor. v0.1 heuristic, not full IFC.