How does Cortex XDR help prevent lateral threat movement?

Cortex XDR plays a crucial role in preventing lateral threat movement by applying machine learning techniques to recognize deviations from normal user behavior. This capability enables Cortex XDR to establish a baseline of typical activities for users and devices within the network. When it identifies any anomalies or deviations from this established norm, which may indicate malicious activity or lateral movement by attackers, it can respond swiftly to contain the threat.

By leveraging machine learning, Cortex XDR can analyze vast amounts of data from various sources—such as endpoint devices, network traffic, and user behavior—to create a more accurate picture of what constitutes normal activity. This proactive approach helps security teams quickly identify and mitigate threats before they can spread laterally across the network, enhancing the overall security posture of the organization.

In this context, the other options do not directly address how Cortex XDR mitigates the risk of lateral movement. Testing traffic for known malware helps identify and block already recognized threats but does not prevent a sophisticated attacker from moving laterally after gaining initial access. Dynamically managing VM-Series firewalls is a valuable function but primarily focuses on perimeter security rather than internal threat movement. Utilizing AI to compare network activity can provide insights but lacks the specific focus on behavior deviations that is essential for preventing lateral movement.