# AAGATE: A NIST AI RMF-Aligned Governance Platform for Agentic AI

arXiv: https://arxiv.org/abs/2510.25863 · HTML: https://mlsanity.com/paper/2510.25863/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 3 of its 15 references that are in the map.
- First posted on arXiv 29 Oct 2025.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 3 of 3)

- [Logic layer Prompt Control Injection (LPCI): A Novel Security Vulnerability Class in Agentic Systems](https://mlsanity.com/paper/2507.10457/) (2025)
- [QSAF: A Novel Mitigation Framework for Cognitive Degradation in Agentic AI](https://mlsanity.com/paper/2507.15330/) (2025)
- [DIRF: A Framework for Digital Identity Protection and Clone Governance in Agentic AI Systems](https://mlsanity.com/paper/2508.01997/) (2025)

## Built on by (most cited first, 3 of 3)

- [AI-GRACE: A Use-Case Operationalization Framework for Agentic AI: From Organizational Objectives and Obligations to Deployment Capabilities and Architecture](https://mlsanity.com/paper/2609.21192/) (2026)
- [Distributed Legal Infrastructure for a Trustworthy Agentic Web](https://mlsanity.com/paper/2603.06884/) (2026)
- [KYA: A Framework-Agnostic Trust Layer for Autonomous Systems with Verifiable Provenance and Hierarchical Policy Composition](https://mlsanity.com/paper/2605.25376/) (2026)

## Abstract (arXiv)

This paper introduces the Agentic AI Governance Assurance & Trust Engine (AAGATE), a Kubernetes-native control plane designed to address the unique security and governance challenges posed by autonomous, language-model-driven agents in production. Recognizing the limitations of traditional Application Security (AppSec) tooling for improvisational, machine-speed systems, AAGATE operationalizes the NIST AI Risk Management Framework (AI RMF). It integrates specialized security frameworks for each RMF function: the Agentic AI Threat Modeling MAESTRO framework for Map, a hybrid of OWASP's AIVSS and SEI's SSVC for Measure, and the Cloud Security Alliance's Agentic AI Red Teaming Guide for Manage. By incorporating a zero-trust service mesh, an explainable policy engine, behavioral analytics, and decentralized accountability hooks, AAGATE provides a continuous, verifiable governance solution for agentic AI, enabling safe, accountable, and scalable deployment. The framework is further extended with DIRF for digital identity rights, LPCI defenses for logic-layer injection, and QSAF monitors for cognitive degradation, ensuring governance spans systemic, adversarial, and ethical risks.