Find out in this report how the two Endpoint Detection and Response (EDR) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Cortex XDR by Palo Alto Networks delivers comprehensive endpoint security, integrating well with other systems to offer robust threat detection and real-time protection through AI-driven analytics.
Cortex XDR by Palo Alto Networks offers advanced endpoint protection and threat detection through AI and behavior-based analytics. Its user-friendly design simplifies integration with firewalls, delivering multi-layered protection with low resource consumption. Valued for policy management, USB control, and incident correlation, Cortex XDR enhances threat management and real-time threat hunting capabilities. However, users note challenges with third-party integration, reporting, and dashboard automation. Agent performance across operating systems and memory consumption are areas for improvement, alongside reducing false positives and simplifying endpoint management and setup.
What features does Cortex XDR offer?Cortex XDR is crucial in industries requiring robust endpoint protection, such as finance, healthcare, and technology. It supports malware detection, behavioral analysis, and ransomware mitigation across endpoints, including remote work environments, providing comprehensive threat visibility and security policy management. The solution's integration with firewalls and specialized industry requirements enhances security posture in diverse operational settings.
Today’s cybercriminals constantly design unique and innovative methods of penetration and compromise. To avoid perimeter prevention technologies they use social engineering, non-malware and supply chain attacks to operate under the radar of security designed to catch ‘bad’ traces. It’s not enough to just ‘know’ what’s bad or dangerous – enterprises need to understand what’s normal, and use AI-driven techniques that simplify and automate this process. Targeted Attack Analyzer is a machine learning engine that involves self-learning to establish the baseline of normal, legitimate activities of an entire network. Through continuous network telemetry collection it finds deviations, detects suspicious activities and predicts further malicious actions at the initial stages of multilayered attacks.
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