The Challenge:
The team at Hulu was tasked with building and operating a world class security program — including corporate security, application security, and physical security — with a relatively small team. Among their challenges were timely incident investigation, understanding where and how their service accounts were being used, and advanced threat detection. Prior to Exabeam, Hulu had used another UEBA solution but they were underwhelmed with the results of that vendor’s correlation rule-based approach to detection.

The Solution:
Exabeam Advanced Analytics provided Hulu with a user and entity behavior analytics solution that ingested and holistically analyzed logs from Hulu’s divergent array of log sources. Through the use of data science and machine learning, Exbeam was able to identify and baseline the normal behavior of both human users and service accounts. Upon detecting malicious or abnormal activity, Exabeam automatically created pre-built incident timelines which presented threats to Hulu’s analyst as easy to absorb stories.

The Result:
Exabeam’s behavioral modeling-based approach yielded vastly improved threat detection compared to the previous UEBA tool Hulu had tested; this meant analysts needed to spend less time validating results. Additionally, Exabeam’s automatically created incident timelines further amplified the productivity of Hulu’s analysts because analysts no longer needed to piece together evidence from disparate log sources to investigate threats. Exabeam Advanced Analytics enabled Hulu to obtain better detection results from their existing security solutions and a higher investigation capacity for their SOC team.

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