Cloud Analytics Platform
Gain full visibility and control over Cloud applications to ensure compliance, access governance, monitor insider activity, and get alerted on anomalous behaviors
With organizations embracing cloud applications, the data is leaving the company perimeter. Organizations now face new challenges including lack of visibility and control to protect their sensitive data, ensure compliance, and on-going governance.
Gurucul’s Cloud Analytics Platform (CAP) is built upon our core architecture PIBAE (Predictive Identity Based Behavior Anomaly Engine) to provide full insight into Cloud applications with contextual views of an identity, it’s access, and associated activity. This powerful approach is able to highlight anomalies which in turn is used to identify insider threats, compromised accounts, compliance violations, data leakage and assist in investigation and forensics. Our Big Data enabled approach along with contextual access, intelligent security analytics, and user behavior modelling can provide an organization with continuous insight into its cloud infrastructure.
- Instantaneous onboarding with no operational complexity
- Out of the box integrations with all cloud applications
- One stop shop to view who has what access to your cloud applications and how is it being used
- Proactive and actionable alerting on anomalous behaviors
- Proactively find data exfiltration
- Meet compliance and governance goals
Powered by Predictive Identity Based Behavior Anomaly Engine that provides:
- Library of Machine Learning Algorithms
- Flexible Meta Data Framework
- Fuzzy Logic Based Identity Correlation
- Most Granular & Self Tuning Risk Modeling Capabilities
- Signature-Less Technology
- Built for Scale Using Big Data Foundation
Gurucul’s Cloud Analytics Platform (CAP) is built upon our core architecture PIBAE to provide full insight into Cloud applications with contextual views of an identity, its access, and associated activity
Purpose Built to Identify Day Zero Anomalies
Self-training algorithms are tailored to identify learned anomalous behaviors immediately upon deploying the technology. (Insider Threat Count Screen)
Detailed Insight into All Anomalous Behaviors – Endpoints, Applications, Devices, and Users
Machine learning algorithms are executed on 254 attributes to build different anomalous behavior profiles across the entities. (Resource Risk Score Screen)
Context Aware Visibility of An Attack Lifecycle
Out of the box timeline view to highlight the anatomy of an advanced attack whether it be an insider or external. (Timeline View) Advanced Visualization & Workflow Centric UI Visually see and analyze the threat for faster incident response and customize the views based on your operational needs. (Custom Visualization Screen)
Situational Awareness with 3rd Party Intelligence Feed and Threat Sharing
Gain additional context by integrating 3rd party feeds and share industry specific threat scenarios. (Share with Healthcare, Finance)
Gurucul is dedicated to transforming the cyber security landscape using machine learning, intelligence-driven, big data security analytics. Using identity as a threat surface, Gurucul provides Actionable Risk Intelligence™ to protect against targeted attacks and under-the-radar cyber campaigns. Gurucul is able to proactively detect, prevent and deter advanced insider threats, fraud, and external threats to system accounts and devices using sophisticated self-learning, advanced behavior and anomaly detection algorithms.
Gurucul is backed by a strong advisory board comprising of fortune 500 CISOs, world renowned experts in government intelligence and cyber security. The company was founded by seasoned entrepreneurs with a proven track record of introducing industry changing enterprise security solutions. Their mission is to deliver rapid results to any organization that desires to protect its intellectual property, regulated information, and brand reputation.