DLT and Sqrrl provide your agency with industry leading threat detection and response platform. Uniting threat hunting, behavioral analytics, and incident investigation capabilities, this unique platform approach enables security analysts to discover threats faster and reduce the time and resources needed to investigate them. Built to streamline the hunting experience as an hunting platform, Sqrrl Enterprise enables your agency to filter and prioritize Big Data while iteratively asking the data questions and explore the relationships in the data.
Sqrrl Enterprise enables the consumption and analysis of disparate datasets to facilitate proactive threat detection, in what’s known as cyber threat hunting. Sqrrl’s Big Data architecture leverages Hadoop, link analysis, machine learning, data-centric security, and advanced graph visualization technology.
Sqrrl is the leading provider of threat hunting solutions. Threat hunting is a proactive and iterative approach to finding advanced attacks that have evaded other defenses. Sqrrl utilizes various Big Data techniques to simplify and automate hunting, which serves as a last layer of defense to prevent catastrophic attacks and data breaches.
Alert Triage and Incident Investigation
Sqrrl automates much of the incident investigation process. Sqrrl pre-defines all the search pathways that analyst may want to explore and can eliminate manual searches. Instead, analysts can easily point and click through linked datasets to conduct their investigations. Sqrrl has improved incident investigation timeframes by an order of magnitude with some of its customers.
User and Entity Behavior Analytics
Sqrrl’s UEBA solution utilizes advanced machine learning and graph algorithms to identify cyber threats that other tools miss. Sqrrl combines these algorithms with a risk scoring framework that prioritizes high risk users and devices, leveraging network, endpoint, threat intelligence, identity, and other security datasets.