How Agentic MXDR can help security teams move from alert-driven operations to continuous, threat-led defense

As organizations adopt AI agents to create an agentic SOC, speed is only part of the equation. The bigger question is how to use autonomous capabilities without losing governance, visibility, or accountability. CyberProof Agentic MXDR is designed for enterprises that need AI-powered security operations with human oversight built in. AI agents help accelerate threat profiling, hunting, investigation, and response workflows, while CyberProof experts validate high-impact decisions and remain accountable for outcomes. This co-managed approach gives security teams transparency into what agents and analysts are doing, where action is being taken, and how risk, time, and cost improvements are being achieved.

Cyber attacks are moving at AI speed, while security operations are often slowed down by manual triage, disconnected tools, and alert overload. CyberProof Agentic MXDR puts AI into action by orchestrating Microsoft, Google, third-party, client-developed, and CyberProof agents across one governed security service. These agents help profile threats, prioritize exposures, hunt, investigate, and prepare response recommendations, while CyberProof experts validate high-impact decisions, manage exceptions, and continuously improve the service.

CyberProof operates the client’s security operations center (SOC), monitoring alerts and investigating potential security incidents across the client’s environment. The SOC handles a high volume of alerts and cases on a daily basis, requiring efficient investigation workflows and consistent escalation processes. The client’s environment includes Google Chronicle SIEM for log management and detection, CrowdStrike for endpoint detection and response, Microsoft Entra for identity management, and Google SecOps SOAR.

In this CyberProof Detection Engineering demo, Vlad Shvartsblat, Detection Engineering team lead, explains how CyberProof is scaling detection engineering across multiple customer environments through a centralized golden repository model. Managing detections across many customers can quickly become complex. Each customer may have its own detection base, logic, tuning, and updates, creating siloed environments that drift apart over time. New detections, improvements, and refinements often need to be propagated manually, which takes valuable engineering time and can create inconsistencies in coverage.

As agentic AI projects proliferate, enterprises are realizing they must approach autonomous systems with the same governance and security rigor applied to other mission-critical systems. Agentic AI workflows involve many agent and MCP interactions between applications, services, and data sources, all with little to no human intervention. These integrations have greatly expanded the attack surface with a proliferation of endpoints that are difficult to discover, govern, and monitor.

In this Agentic MXDR demo, we show how CyberProof uses agentic AI to validate detection rules and identify logic issues that may prevent rules from triggering. Security teams often manage hundreds of detection rules, but not every rule is working as expected. In this demo, you will see how the agent reviews detection history, analyzes rule logic, and generates a report showing which rules are not triggering and why. The agent can identify straightforward issues, such as missing log source data, as well as more complex logic problems that would be difficult and time-consuming for analysts to test manually.

In this Agentic MXDR demo, we introduce CyberProof’s GRC Agent, an agentic AI tool designed to transform how organizations perform compliance gap analysis. Traditional gap analysis against frameworks like ISO 27001 can take weeks or even months, and results may vary depending on the consultant performing the assessment. CyberProof’s GRC Agent helps make the process faster, more consistent, and more scalable by using agentic AI to analyze policy documents, map them to framework controls and clauses, identify compliance gaps, and generate remediation guidance.