ExtraHop, a network detection and response provider, has announced new capabilities designed to support AI-driven security operations centres. The company is providing network intelligence and forensic tools to enable AI agents to operate autonomously in threat detection and response. The platform now integrates with identity systems including Entra ID, Active Directory and Okta, combining user data with network telemetry. ExtraHop has also added visibility into Kubernetes environments and introduced the ExtraHop Query Language, allowing AI agents to query network data through APIs and Model Context Protocol servers. The updates aim to provide the contextual data required for AI agents to triage and respond to cyberthreats independently, addressing what the company describes as a critical gap in autonomous security operations.

ExtraHop, a network detection and response provider, has announced new visibility and forensic capabilities designed to support autonomous AI agents in security operations centres. The company is addressing the challenge of providing AI agents with contextual insights needed to operate independently against cyber threats. The platform now integrates with identity systems including Entra ID, Active Directory and Okta, combining identity attributes with network telemetry. ExtraHop has also added full visibility into Kubernetes environments and introduced the ExtraHop Query Language, enabling AI agents to query network telemetry at machine speed. The company uses deep protocol analysis to correlate activity across devices, users, applications and identities, providing context for AI agents to autonomously triage and respond to threats. ExtraHop positions network data as essential fuel for enterprise agentic operations.

ExtraHop expands NDR platform to fuel autonomous SOC operations. New identity integrations, Kubernetes visibility and query capabilities aim to close context gaps for AI-driven security teams Source SecurityInfoWatch.com Related To: Feb. 12, 2026 Key highlights. * Enhanced integration with identity platforms like Microsoft Entra ID, Active Directory, and Okta provides clearer insights into user actions and reduces ambiguity for AI agents. * New Kubernetes visibility features decrypt traffic and analyze resource metadata, closing security gaps in containerized and cloud-native environments. * Secure API and Query Language (EQL) access enable AI agents to perform real-time data queries, improving automated detection and response capabilities. * ExtraHop emphasizes the importance of high-fidelity, contextual data as a foundation for effective autonomous security operations. ExtraHop has rolled out new visibility and forensic capabilities designed to support the rise of the "agentic SOC," where AI agents augment or automate key elements of threat detection and response. The Seattle-based network detection and response (NDR) provider said the enhancements are intended to deliver the high-fidelity network intelligence required for autonomous security operations to function effectively, particularly as AI-assisted attacks increase in scale and sophistication. As organizations deploy AI agents to help offset staffing shortages and operational complexity, many are discovering that automation alone is not enough. Without comprehensive, contextual data on anomalous and malicious activity, AI-driven workflows can stall or generate unreliable outcomes.