The Challenge of Non-Deterministic AI
The rapid adoption of artificial intelligence agents and applications has created a major security challenge for enterprises. Unlike traditional software, which follows defined rules, AI systems are non-deterministic and behave unpredictably. This fundamental shift breaks the security assumptions that have guided software protection for decades. Niv Braun, CEO of Noma Security, warns that the pressure to deploy AI quickly leaves security teams struggling to keep pace, while the potential blast radius of a compromised AI agent is enormous.
Context and Runtime Visibility as Keystones
To address these risks, security strategies must evolve beyond traditional approaches. Braun argues for a holistic framework that can absorb fast-moving technologies like the Model Context Protocol (MCP). The key is deep contextualization that unifies posture management, access controls, and runtime monitoring into a single signal. Without visibility into what happens during runtime, it is impossible to provide good recommendations on configuration or access controls. Understanding which agent actions are legitimate versus which represent real risk requires continuous monitoring and a security platform that does not rely on siloed point products.
Source: Healthcareinfosecurity
