Security
Protect against unknown threats with user and entity behavior analytics.
Splunk User Behavior Analytics uses unsupervised machine learning algorithms to establish baseline behaviors of users, devices, and applications, then searches for deviations to detect unknown and insider threats.
Splunk User Behavior Analytics visualizes threats across multiple phases of an attack to give security analysts a comprehensive understanding of attack root cause, scope, severity, and timelines. This context-rich view enables analysts to rapidly assess impact, and make informed decisions quickly and confidently.
Splunk User Behavior Analytics automatically reduces billions of raw events down to tens of threats for rapid review, without the need for time-consuming human-fueled detective work performed by highly skilled security and data science professionals.
Reduce billions of raw events to tens of threats for quick review and resolution. Use machine learning algorithms to help identify hidden threats without human analysis.
Visualize threats over a kill chain to gain context. Anomalies are stitched together across users, accounts, devices, and applications so you can clearly see attack patterns.
Customize anomaly models based on your organization’s processes, policies, assets, user roles, and functions. Get granular feedback to improve confidence in threat severity and detection.
Detect lateral movement of malware or malicious insider proliferation. See behavior-based irregularities or pinpoint botnet or C&C activity.
Splunk UBA is giving us deep insight into our insider threat and what our trusted users are doing at any given instant.
Automatically detect and analyze the most complex credential phishing and malware threats.
Proactive risk mitigation through continuous asset discovery and compliance monitoring.
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