A secure low code honeypot framework, leveraging AI for System Virtualization.
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Updated
Mar 24, 2026 - Go
A secure low code honeypot framework, leveraging AI for System Virtualization.
AI Security Platform: Defense (61 Rust engines + Micro-Model Swarm) + Offense (39K+ payloads)
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.
The definitive open-source reference for AI Trust, Risk, and Security Management (AI TRiSM). 60+ vendor profiles, market sizing, regulatory tracking, and Gartner framework analysis. Structured for machine readability and AI-system extraction.
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.
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.
An experiment in backdooring a shell safety classifier by planting a hidden trigger in its training data.
TypeScript/JavaScript SDK for AI Agent Security - Drop-in security for LangChain, CrewAI, AutoGPT and custom agents
Enforce agent actions with policy checks and cryptographic receipts to prove compliance and enable independent verification.
Signed receipts for agent/tool actions. PolicyGate enforces allow/deny; every decision emits a tamper-evident receipt with hashes, signatures, and optional approvals. Verify in CI, prove what happened, and make agent integrations survivable in regulated environments.
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