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DatAlert Analytics and the Varonis Behavior Research Laboratory

DatAlert Analytics and the Varonis Behavior Research Laboratory

Last November, we introduced Varonis UBA threat models to automatically analyze behavior and detect insider threats throughout the lifecycle of a breach.  Our UBA threat models, which are major enhancements to Varonis DatAlert and are in beta availability, have been helping our customers protect their data – from spotting signs of ransomware activity to catching unusual activity on sensitive data.

But with news of more data breaches rolling out every day and brand new variants of ransomware popping up all the time, how can you keep up?

We’ve established a professional behavior research laboratory for just that reason.

Security experts and data scientists from Varonis now continually introduce new behavior-based threat models as part of DatAlert Analytics, keeping you up-to-date with the latest in security issues, APTs, and insider threats. This dedicated team is focused exclusively on creating new threat models to better protect your data, including privileged and service account detection and integration with all up-to-date malware and crypto repositories.

As insider threats become more sophisticated, so do our security tactics.  Some of the things our experts will focus on in the coming months include:

  • Account detection and auto-profiling, so you can automatically detect executive accounts and see unauthorized attempts to gain access to c-level data.
  • Threat models designed to alert on new variants of CryptoLocker so you can spot ransomware attacks before they get out of hand.
  • Threat models that detect mass deletes and lockout activity so you can find out when somebody’s attempting to damage or destroy data before it’s gone.

DatAlert Analytics is like having your very own behavior research laboratory to stay on top of the latest in security attacks and develop more ways to fight back against insider threats. Want to get see DatAlert Analytics in action?  Get in touch.

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