Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Risk in the agentic enterprise spans people, service accounts, and AI agents. All three act with legitimate credentials, so access controls alone can’t show whether their activity is safe. A behavioral risk framework applies one model to every actor: Verify expected behavior before access goes live, observe activity once it does, analyze behavior for risk and drift, and improve detection coverage over time.

A security leader finishes a pitch to the board about an agentic SOC that pairs AI agents with analysts to address the coverage gap. A hand goes up. “So, the AI decides who’s a threat?” It’s a fair question. It’s also the wrong one, built on a myth that’s common enough to stall adoption on its own.

CISOs need an agentic SOC strategy because traditional staffing models can’t scale to match machine-speed threats, a global talent shortage, and rising alert volume. An agentic SOC pairs AI agents that collect evidence and investigate at machine speed with analysts who provide judgment, context, and accountability. Exabeam combines Agent Behavior Analytics (ABA), Exabeam Nova AI, and automated investigation to expand coverage and speed response without adding headcount.

Exabeam delivers stronger detection, faster investigations, and more flexible deployment than IBM QRadar and Cortex XSIAM. It combines user and entity behavior analytics (UEBA), Agent Behavior Analytics (ABA), and agentic AI through Exabeam Nova AI to reduce alert noise and automate workflows. With cloud-native capabilities in New-Scale Fusion, Exabeam gives security teams a modern approach to SIEM and security operations.

The October 2026 LogRhythm SIEM release modernizes self-hosted security operations with an in-place migration from Elasticsearch to OpenSearch, a next-generation self-service reporting engine, generative AI collectors, and a community Model Context Protocol (MCP) server. The release also includes backend and API updates that improve event drilldown, rule administration, network routing, and telemetry quality while helping organizations maintain control of sensitive security data.

An agentic SOC uses AI-powered investigation, analysis, and automation to gather data, connect activity, and handle repetitive investigative work. Analysts remain in control and focus on judgment, prioritization, and response. This addresses the need for machine-speed security operations as AI agents gain autonomy and Tier 1 access to systems. Spend five minutes watching a security analyst at work and the “AI will replace analysts” headline starts to sound out of touch.

Last week I wrote a piece talking about OpenAI’s misalignment blog and how it was a flashing red neon sign for security teams.

AI Agents are no longer the new insider threat. They’ve become firmly planted as the primary challenge for security leaders when it comes to insider threat activity. They have credentials, they act autonomously, and increasingly, they can take real actions on real systems. How would you know when one of your digital workers starts doing something it’s never done before?