UEBA partaking in collection of relevant information contributes to prompt issue detection and extends SIEM* and other risk mitigation solutions’ functionality by in-depth involvement into incident response and management with the help of machine learning and other analytics methods.

* According to the Market Guide by Gartner, UEBA will discontinue its presence as a stand-alone market and will exist as UEBA features embedded in a SIEM and other analytics instruments.

Project risk management program requires access to information concerning user behavior, and intelligent UEBA techniques provide you with details about suspicious events.

Combining User and Entity Behavior Analytics, the automated technology saves time on a violation source detection and eliminates the possibility of false alarm as UEBA models both user and system behavior monitoring how they correlate and alerting only to a repeated event or proven threat.


Operates as an early warning system discovering a potential threat or a precondition for a violation and alerting to possible risks by detecting a number of abnormal activity episodes outside or inside the corporate network.

Guards against external anomalies:

Reveals users going beyond an established behavioral pattern due to external violators who log into the users’ accounts and affect their work activity

Guards against internal threats:

Prevents password sharing and misuse of accounts by insiders, protects employees from harassment and nepotism in the workplace


UEBA features highlights

  • Complete insight into user/entity correlation
  • Automated investigation with Machine Learning techniques
  • Protected data can be accessed only in case of a specific assignment within an established role and task
  • Intelligent technology eliminates false positives during event processing and incident reporting

SearchInform user behavior analytics intelligence links and connects entities with events which get tracked in accordance with user roles and responsibilities, established organizational policies and baselines.

User and Entity Behavior Analytics studies standard accepted behavior patterns to develop a baseline in accordance with which a wrongdoer can be detected.

Baselines created by the system allow the self-learning solution to process appropriate user behavioral patterns and emphasize tendencies and potential internal threats.

Privacy by design - privacy of an individual is respected – identification is permitted only when the analyzed activity reveals a sequence of events which threatens a company. Automated analysis eliminates misconduct of available data sets.

The strong and solid convergence of UEBA and SIEM is one of the solution’s most comprehensive mechanisms which modernizes SIEM upgrading its analytics capabilities

Addresses many use cases

Discovers anomalies with the help of various analytics approaches

Policy presets and use case templates take into account the experience of companies from a wide range of industries

Gathers information almost from every source (from event logs of servers and workstations to network active equipment and virtualization environments)

Correlates unrelated data – there are situations when events, seemingly harmless, together can pose a greater threat. For example, when someone sends a password to a top manager’s account, this user will not attract attention but, if later this account accesses critical resources, the system will alert to the incident


Risk Monitor

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The provider guarantees that first results are obtained as soon as the company’s solution is installed – pre-configured settings are sufficient to begin with.

The deployment and implementation process does not require any programming skills. An expert will be able to customize the software. There is no need to create scripts and write event correlation rules because the solution is supplied with a set of versatile policies.


Internal threat detection based on analysis of correlation between users and entities

Unauthorized access identification and privileged user activity monitoring

Fraud discovery and employee monitoring*

Malicious insider activity, abusive behavior based on unstructured information (for example, correspondence content)


Incident prioritization algorithm adaptable to an organization’s structure

Privileged access management, excessive privileges identification


Sabotage and advanced threats


*as EM systems imply collecting such information as screenshots, video recorded screen activity, correspondence analysis, UEBA ensures data safety and compliance to regulatory requirements regarding personal data usage


  • Risk Managers

    User activity monitoring, data usage and storage by contractors and third parties

  • Security Operations Center

    Activity inside and outside a company’s perimeter, abnormal user activity due to an external breach of a user account

An employee of a major healthcare institution gained access to private data although he was unauthorised to read and copy this information. UEBA facilitated detection of unsanctioned activity and alerted to an event which was beyond a baseline behavior model. It was revealed that a system administrator gave the employee temporary access to the customer database.

If there was no UEBA solution, the data protection software would only inform about the employee’s attempt of the further data upload to a USB drive, for example, or of sending it by email.


of employees who were reassigned to other jobs still have access to the data which isn’t related to their new tasks


admitted that irrelevant access rights aren’t terminated when employees are shifted to do different jobs

The solution learns patterns and helps to detect personal data in traffic even if its content is altered.

Usage of UEBA ensures data privacy, excludes risks concerning legal issues during personal data collection, analysis and storage.

PCI DSS, Basel, HIPAA and full GDPR compliance support.

Guarantees confidentiality and responsible use of customer nonpublic information and PHI (Protected Health Information).

Controls access rights differentiation and delimits roles of users authorized to work with particular data.

Shapes behavior of users accessing and processing personal data and detects any discrepancy or deviation.

Manages and examines newly created and current accounts in order to discover identity theft as early as possible.

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