Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Cybersecurity has spent decades learning how to distinguish trusted users from attackers. The agentic enterprise complicates that model. An AI agent can be trusted, authenticated, authorized, and functioning as designed, yet still produce an unintended or risky outcome through a sequence of otherwise legitimate actions. That scenario does not require a malicious agent.

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.

Every Operating System – not even counting the software installed on top of it – has a myriad of configuration settings that affect security. Windows Server alone has 4000+ configurable options, out of which 200+ are important for security & compliance efforts. They include: These settings are at the very core of all of your security & compliance efforts – and they are surprisingly often ignored.

The rules of cyber defense have shifted. Threat actors are increasingly using advanced automation to accelerate reconnaissance, evade static signatures, and orchestrate rapid intrusions across critical infrastructure, software supply chains, and insider pathways. This has created a critical velocity gap: when adversaries compress attack timelines from days to minutes and defenders rely on manual triage across fragmented legacy tools, the defense falls behind.

The future of policing depends on more than changing force structures or investing in AI. It depends on making data work across boundaries. Policing is being asked to change at pace.

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.