Veriato Cerebral

Veriato Cerebral is an AI-powered security platform that integrates User & Entity Behavior Analytics (UEBA) with User Activity Monitoring (UAM), allowing rapid Data Breach Response (DBR). The product enables to rapidly detect insider threats from employees, estimate their productivity, gather evidence essential and immediately take actions.


  • Records, and maintains information about web activity, including webmail usage, file uploads, and how long a user was engaged or active on a site.
  • Monitors access to workstations and servers for unusual access by IP addresses, geolocation, and more.
  • Capture communications activity in traditional email clients as well as many popular webmail services.
  • Capture, scan, alert and report on communications activity occurring on commonly used messaging apps; creates a definitive record for compliance and investigative uses.
  • Using computational linguistic analysis, Cerebral can identify and categorize opinions expressed in email text, to determine the writer’s sentiment and sentiment changes that can point towards disgruntled workers and possible security risks.
  • Autonomously captures connections made by applications, including ports used and bandwidth consumed as well as time and location of connection.
  • Tracks activities on local, removable, and cloud storage, as well as print operations. See when files are created, edited, deleted, or renamed.
  • When needed, the option to record every keystroke, including “hidden” characters and combinations, insures you have the visibility you need into the activity of highly privileged users.
  • Captures all application usage to provide true reporting on what applications are open, being actively used, by who, and for how long.
  • Data on the location of an Android device can be tracked as well as configured to alert security when a user device enters a restricted location or moves outside a specified geographic area.
  • Produces an accurate record of session time and activity. Tracks logon and logoff but does not rely on logoff to identify when session activity ends.
  • Get alerted when employees access the Dark Web using the Tor Browser.
  • Builds a comprehensive risk score for each user on a network.
  • Detects deviations from established patterns enabling early warning of insider threats.
  • Self-learning of behavioral patterns for individuals and groups, driven by advanced machine learning, enables no-touch understanding of what normal looks like for everyone in your environment.

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