Innspark UEBA

Never miss any threatening behavior from inside

Unparalleled detection of malicious insider activities using deep insights around users and threats

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Detection of hijacked accounts


Multi-user attack detection


Improved Operational efficiency


Data exfiltration detection


Priviledge Abuse and misuse


Lateral movement detection

Innspark Capabilities

Increased Anomaly Detection

Innspark’s UEBA solution provides real-time monitoring of all ingested logs and alerts on any anomalous variations in user behaviour. Each deployed UEBA model undergoes a training period to establish a baseline, and once any deviations/ breach from that baseline are detected, UEBA alerts the variation and reports the relevant contextual information

Smart User Activity Timeline

Innspark’s UEBA (User and Entity Behavior Analytics) solution constantly monitors the actions of each user, creating a detailed timeline of their activities that provides analysts with all the information they need to investigate an incident. The timeline is automatically populated in chronological order, and the system is capable of monitoring the activities of up to 5000 users simultaneously. With Innspark UEBA, organisations can gain real-time visibility into user behaviour and detect anomalies that may indicate potential security threats

Machine Learning & Artificial Intelligence

Innspark UEBA leverages a wide range of machine learning modules, including Reinforcement Learning, Deep Learning, Supervised Machine Learning, Bayesian Networks, and various other models based on time, category, and continuity, as well as discrete models

Blazing Fast Forensics

The system supports forensics search across both RAW and Parsed data using natural language through an intuitive GUI interface, which makes it user-friendly. The system provides compatible options and auto-suggests based on contextual data when each field is selected, ensuring ease of use for analysts

User Interface & Dashboards

 Innspark UEBA solution offers intuitive and operationally-friendly visualisations that provide valuable insights into the security posture of the organisation. The alerts specific to a tenant/group can be viewed separately, and the dashboards can be configured to display real-time data or to travel back in time to view data for a specific duration

Advanced Threat Detection

Innspark UEBA platform offers comprehensive threat detection capabilities for various malicious activities, including Lateral Movement, Data Exfiltration, Anomalous Data Access, Brute Force detection, Insider Threat detection, and Network Behavioral-based detections, right out-of-the-box. Additionally, the system proactively monitors for privilege misuse activities, such as account sharing, takeover, and hijacking


Innspark UEBA is designed to enhance the security posture of organizations by integrating with various security solutions, including SIEM, SOAR, EDR, and XDR. Its key features include:

  • High accuracy machine identification, even if IP addresses change

  • Granular role-based access control (RBAC)

  • One-click export of raw log data

  • Alert mechanism for threat detection

  • Integration with enterprise authentication systems

  • Auto identification of trusted hosts and compromised entities

  • Optimizable risk models for better threat detection

  • Auto identification and classification of users and entities

  • Support for high availability (HA) architecture

      • Fine-tuning of metadata attributes for behaviour models

      • Dedicated report generation engine with built-in templates for exporting reports in PDF, CSV, and Excel formats

      • Automatic report generation through scheduling

      • Web-based application for easy access

      • Supports creation of custom models and rules/policies that can be automatically adjusted through automated learning

      • Self-learning behavioural analysis to dynamically model each device

      • Retraining of the model based on feedback from security analytics

      • Flexibility to configure rolling window of period for behaviour profiling

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