# Securing Agentic AI Systems -- A Multilayer Security Framework

arXiv: https://arxiv.org/abs/2512.18043 · HTML: https://mlsanity.com/paper/2512.18043/

## 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 1 of its 38 references that are in the map.
- First posted on arXiv 19 Dec 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, 1 of 1)

- [A Model of Pathways to Artificial Superintelligence Catastrophe for Risk and Decision Analysis](https://mlsanity.com/paper/1607.07730/) (2016)

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

- [The Authorization-Execution Gap Is a Major Safety and Security Problem in Open-World Agents](https://mlsanity.com/paper/2605.11003/) (2026)
- [Agentic AI for Cybersecurity: A Meta-Cognitive Architecture for Governable Autonomy](https://mlsanity.com/paper/2602.11897/) (2026)
- [Signals in the Noise: Open Source Intelligence (OSINT) for AI Loss of Control Detection](https://mlsanity.com/paper/2606.20610/) (2026)

## Abstract (arXiv)

Securing Agentic Artificial Intelligence (AI) systems requires addressing the complex cyber risks introduced by autonomous, decision-making, and adaptive behaviors. Agentic AI systems are increasingly deployed across industries, organizations, and critical sectors such as cybersecurity, finance, and healthcare. However, their autonomy introduces unique security challenges, including unauthorized actions, adversarial manipulation, and dynamic environmental interactions. Existing AI security frameworks do not adequately address these challenges or the unique nuances of agentic AI. This research develops a lifecycle-aware security framework specifically designed for agentic AI systems using the Design Science Research (DSR) methodology. The paper introduces MAAIS, an agentic security framework, and the agentic AI CIAA (Confidentiality, Integrity, Availability, and Accountability) concept. MAAIS integrates multiple defense layers to maintain CIAA across the AI lifecycle. Framework validation is conducted by mapping with the established MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) AI tactics. The study contributes a structured, standardized, and framework-based approach for the secure deployment and governance of agentic AI in enterprise environments. This framework is intended for enterprise CISOs, security, AI platform, and engineering teams and offers a detailed step-by-step approach to securing agentic AI workloads.