The Challenge of Non Deterministic AI
The rapid adoption of artificial intelligence agents and applications is creating a perfect storm for enterprise security teams. Unlike classic deterministic software, AI systems do not always behave as defined, breaking the traditional security contract. This unpredictability dramatically expands the potential blast radius of any incident, all while business pressure to deploy quickly leaves security teams struggling to keep pace. Niv Braun, CEO of Noma Security, argues that this new reality forces a fundamental shift in how organizations approach protection.
A Unified Framework Built on Runtime Visibility
To address these unique risks, Braun advocates for a security strategy built on two pillars: a flexible, holistic framework that can absorb fast evolving technologies like the Model Context Protocol (MCP), and deep contextualization that links posture management, access controls, and runtime monitoring. Without visibility into what happens during runtime, he warns, security teams cannot provide accurate recommendations for configuration or access permissions for an AI agent. A unified platform that correlates these elements outperforms siloed point products, enabling organizations to distinguish legitimate agent actions from genuine threats.
Source: Healthcareinfosecurity
