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The integration between Cortex Xpanse and Cortex XSOAR benefits security teams by enabling automatic incident response actions for internet-based incidents. This integration allows security teams to automate the detection, investigation, and response to threats identified through internet-facing assets, improving efficiency and reducing response time.

Cortex Xpanse uses continuous internet scanning to identify previously unknown assets. This feature allows the platform to continuously monitor the internet for new or unregistered assets that could be associated with an organization's network, providing real-time visibility into potential exposure or vulnerabilities.

The primary purpose of Cortex XSIAM's machine learning-led design is to automate the handling of the bulk of incidents. By leveraging machine learning, it can automatically classify, group, and respond to incidents, reducing the need for manual intervention and increasing efficiency in incident management.

Deploying the Cortex XDR agent during a Cortex XSIAM proof of value (POV) is important because it provides telemetry for stitching and analytics. The agent collects endpoint data that is essential for detecting and correlating threats, enabling advanced analytics and providing the necessary context to improve incident response and decision-making in the security environment.

The integration of Attack Surface Management (ASM) in Cortex XSIAM enriches incidents with ASM data for all internet-facing assets, providing a unified approach to security event management. This integration helps identify and address vulnerabilities related to external assets, offering more context and enhancing the overall security incident response. Traditional SIEMs typically lack this level of integration with external asset visibility.

The Data Ingestion Health page provides visibility into the normal patterns of log collection and highlights any deviations, which helps identify issues early on.

he Cortex XSIAM Command Center dashboard displays a red icon when there is an issue with a data source, providing a quick visual indication of ingestion problems.

The feature in Cortex XSIAM that helps analysts reduce the noise and false positives typically seen in traditional SIEM systems is AI-generated correlation rules. These rules use machine learning to automatically identify meaningful patterns and reduce irrelevant alerts, helping analysts focus on the most critical incidents.