Identity, AI/ML

Better identity threat detection sought by new Semperis ML-based tool

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SiliconAngle reports that more robust high-risk identity threat discovery and response efforts are being aimed by enterprise identity protection startup Semperis with its new machine learning-based Lightning Identity Runtime Protection identity threat detection and response service.

ML algorithms based on Semperis' response to identity attacks, including password spraying and credential stuffing intrusions, have been leveraged to train Lightning IRP, which monitors directory change tracking data in hybrid Active Directory and Entra ID environments, as well as attack path analysis and various exposure and compromise indicators to hasten responses to identity threats, according to Semperis.

"Detecting an anomaly is relatively easy. Putting it into context is where the challenge is. We've combined deep machine learning expertise with our first-hand knowledge of how real-life identity system attacks work to provide meaningful context that helps organizations isolate and address high-risk threats," said Semperis CEO Mickey Bresman.

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