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"Our customers need robust, lightweight, and unobtrusive protection against zero-day attacks and can no longer rely on signature or heuristics-based solutions to keep up with the quickly evolving threat landscape," said Bryan Lares, Director of Product Management. "Shifting to DeepArmor's predictive security model enables sec-ops teams to simultaneously reduce the risk of successful attack and eliminate cumbersome signature updates and full system scans."

The new product release adds support for Linux OS with a new agent and machine learning detection engine for malware attacks, supporting the DeepArmor mission to make every system more secure. The headless agent will operate seamlessly in the background, matching existing Mac and Windows capabilities that protect against zero-day malware, script, and weaponized document attacks.

DeepArmor is also expanding telemetry and adding autonomous alert handling to its cloud-based management console. These features leverage DeepArmor's cloud intelligence engine to reduce the workload of the security analyst by automatically taking action on some alerts and reducing false positives. This enables security operations teams to make informed decisions based on system information at the time of the event and key data points extracted during static file analysis.
SparkCognition adds new AI-built cyber defense capabilities to major DeepArmorⓇ v2.0 release
 
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