Threats are a moving target. Determined and persistent threat actors purposely stretch out their activity across weeks or even months, especially when most SIEM and XDR solutions are incapable of piecing together events across time. Even worse, is that these solutions primarily use rule-based Machine Learning, which is essentially pattern matching. This makes them especially ineffective in detecting new attacks and/or variants, which are highly successful in breaching organizations. Discover how Gurucul UEBA security can help your enterprise.
Identify high-risk profiles with risk-based user and entity behavior analytics, data mining, anomaly, and behavior detection. Help security teams by creating a baseline using profiling attributes from HR records, events, access repository, log management solutions and more.
Our UEBA solution detects attacks using ML algorithms tuned to inspect various parameters like timestamp, location, IP address, device, transaction patterns, high-risk events codes and network packets. Identify any deviation from the normal behavior that may be indicative of a threat.
Detect advanced persistent threat (APT) attacks and attack vector and predict data exfiltration by performing entity-centric anomaly detection with our UEBA solution. Correlate a wide range of parameters incluiding endpoint security alerts, vulnerability scan results, risk levels of users and accounts used, targets accessed, packet level inspection oh the requested payload, and more.
Gurucul UEBA can detect techniques used by threat actors as part of an attack campaign. Identify unusual activity and suspicious access as threat actors attempt to traverse the network in search of finding better vantage points to download additional malware, communicate to external servers, and eventually find the location of sensitive data.
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