Gurucul Risk Analytics
Predictive Security Analytics to Detect Unknown Threats and Reduce Access Risks
Gurucul Risk Analytics (GRA) is a Unified Security and Risk Analytics platform on open choice of big data. GRA leverages over 1500 Machine Learning Models powered by data science to produce actionable risk intelligence. GRA does not rely on signatures, rules or patterns. It is intended – from the ground up – to identify zero-day threats and is designed to provide both contextual and situational awareness.
Gurucul Risk Analytics detects and stops malicious behavior before cyber criminals or rogue insiders can do harm. GRA is the only security analytics platform that can ingest all data sources out-of-the-box. It can ingest data from any source, including proprietary business applications, to give you the most accurate 360-degree view of a user’s or entity’s behavior. In addition, GRA runs on your choice of big data platform: Hadoop, Cloudera, Hortonworks, Amazon EMR and more. If you don’t have a data lake, GRA comes with Hadoop for free – for use with the platform.
Gurucul Risk Analytics leverages a comprehensive risk engine which performs continuous risk scoring based on historical and current behavior. GRA provides real-time risk prioritized alerts for incident investigation and analysis. These dynamic unified risk scores can be used to trigger automated risk-response workflows. GRA provides playbooks to facilitate Security Orchestration Automation and Response (SOAR). In addition, the platform integrates with many third party SOAR solutions out-of-the-box.
Gurucul Risk Analytics leverages Gurucul Data MineTM, an open source big data backend. Gurucul Data MineTM is used to correlate, link and store data from applications, platforms, NetFlow, threat intelligence, and other security solutions. GRA uses this contextual information for machine learning, behavior analytics and deep learning.
The Gurucul Risk Analytics platform powers the full suite of Gurucul cybersecurity products: Unified Security Analytics, User and Entity Behavior Analytics (UEBA), Network Traffic Analysis, Identity Analytics and Fraud Analytics.
Why Choose Gurucul Risk Analytics?
Gurucul offers advanced security analytics that goes beyond the traditional rules-based detective controls. GRA leverages big data and advanced machine learning algorithms to predict, detect and prevent insider threats, access outliers and cyber fraud in enterprise and cloud environments.
Model good behavior to expose unknown bad behavior through peer groups, clustering and outliers.
Analyze access and its abuse with identity-centric behavior analytics from big data.
Modify our analytics or build your own with Gurucul STUDIOTM.
Provide behavior analytics for on-premises and cloud application hybrid deployments.
Detect insider threats, account hijacking, data exfiltration and cyber fraud.
Leverage predictive security analytics to risk-score incidents and drive ‘find-fix’ focus.
Gurucul Risk Analytics Capabilities
Largest library of prepackaged machine learning models and the ability to build your own
Enterprise Risk Engine
Drive risk-based security controls and define risk your way
Alerting & Case Management
Comprehensive case management capabilities and alerting techniques
Dashboards & Reporting
Widget driven configurable dashboards and reporting for security operations, audit & compliance
Natural language contextual search for investigations
Response workflows for automated risk remediation
Create custom machine learning models without coding and needing only a minimal knowledge of data science. Gurucul STUDIOTM provides a step-by-step graphical interface to select attributes, train models, create baselines, set prediction thresholds and define feedback loops. As part of Gurucul Risk Analytics (GRA), STUDIOTM supports an open choice for big data and a flex data connector to ingest any on-premises or cloud data source. Step outside the black box and create custom models for your own predictive security analytics needs.
“Gurucul Risk Analytics reduced the number of accounts and entitlements by 83%, plus defined intelligent roles and provided dynamic access provisioning, using a behavior-based risk context.”
– AVP Cyber Security, IT Services Company