Securonix has announced a major expansion of its Unified Defense SIEM platform, introducing Governed AI Agent Detection and Response, enhanced Threat Analytics for Microsoft Sentinel, and expanded Data Pipeline Manager (DPM) capabilities. The updates are designed to help enterprises strengthen security operations, manage rising SIEM costs, and securely govern AI-powered workflows as organizations accelerate AI adoption.
One of the key additions is Governed AI Agent Detection and Response, which enables security teams to monitor and investigate the activities of AI assistants, autonomous workflows, and digital workers. The capability provides visibility into how AI agents access applications, interact with sensitive data, and perform actions across enterprise environments, helping organizations identify abnormal behavior and mitigate emerging AI-related security risks.
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Securonix has also expanded Threat Analytics for Microsoft Sentinel, adding advanced behavioral analytics, user and entity behavior analytics (UEBA), risk scoring, and threat intelligence to Microsoft’s cloud-native SIEM platform. The integration enhances detection coverage for identity attacks, insider threats, ransomware, cloud compromises, and advanced persistent threats without requiring customers to deploy additional agents or duplicate security data.
In addition, the company has broadened licensing for its Data Pipeline Manager (DPM) and introduced the DPM Agent, enabling organizations to optimize how security telemetry is collected, routed, stored, and analyzed. The enhancements are designed to reduce SIEM data costs while preserving access to critical security data for threat hunting, investigations, and regulatory compliance.
The latest platform enhancements reflect the growing convergence of AI, cybersecurity, and security operations as enterprises manage increasingly complex hybrid environments. By combining AI agent governance, advanced analytics, and cost-efficient data management, Securonix aims to help organizations improve cyber resilience, simplify security operations, and securely scale enterprise AI adoption without increasing operational complexity.
