Adlumin UEBA for Threat Hunting

Illuminate threats with machine speed and transparency

Adlumin’s User & Entity Behavior Analytics (UEBA) is constantly analyzing your security and operational data to enable quick action in line with emerging risk contexts. It lights up threats to enable a successful hunt.

Blue Swoosh UEBA

Stay ahead of threats. Eliminate risks.

The more data a security organization and hunt team have at their fingertips, the more breadcrumbs and clues they can find. The challenge can be sighting through them quickly enough to get in front of attacks. Threat hunting teams need speed, scale, and clear context to pursue threats from within and those in the dark corners of the Internet. Adlumin’s UEBA machine learning turns up the power on your security risk searchlight.

How does Adlumin’s UEBA enable threat hunting?

Adlumin’s cloud-native streaming analytics platform is designed to discover threats, malfunctions, and IT operations failures across any log data stream. Data from individual users and entities, like servers, workstations, and endpoints can be ingested into the application for baselining expected behavior.

Deviations from these baselines can signal cyberattacks and other events requiring attention.

Immediate Action Required

UEBA-based Threat Hunting Benefits

Powerful Technology

Adlumin’s machine learning techniques are based on the latest graph-theoretic metrics and cluster analysis, like Principal Components Analysis, K-Nearest-Neighbors (KNN) and Cluster-Based Local Outlier Factor (CBLOF).

Transparent Insights

But that powerful machine learning doesn’t live inside a black box. The moment something anomalous occurs, your security team is alerted with transparent justification and a prioritized response plan.

Human-Directed Action

So you can trust Adlumin to give you the best information while your security team makes the right decisions. Or enable security orchestration and response (SOAR) to enable faster, security-designed action.

Adlumin UEBA Threat Hunting Features

Full Network Visibility
Limitless Data
Behavioral Patterns
Total Metric Visualization
Smarter, Quieter Alerts
Threat Hunting-Full Network Visibility

Adlumin delivers end-to-end visibility into incoming data records through the detection process, giving the user control over the detection and surveillance capability via state-of-the-art and intuitive entry points.

Threat Hunting-Limitless Data

Our hyper-scalable, patented architecture for ingesting streaming data means the platform updates machine learning algorithms for anomaly detection across an infinite quantity of data streams to discover threats, malfunctions, IT operations failures, and other predictive analytics use cases.

Threat Hunting-Behavioral Patterns

Autonomous parsing of streaming data using advanced algorithms detects anomalous events by efficiently learning baseline maps of normal messages, utilizing techniques that are especially scalable for cloud computing environments.

Adlumin visualizes usage, web, and project execution metrics from any system, including Jenkins, using isolation forest and other tree-based techniques within the umbrella of unsupervised machine learning, allowing AF users to direct investigative or analyze resources effectively.

Threat Hunting-Smarter Quieter Alerts

Adlumin’s model user command executions lead to detections of abnormal executions without excessive false positives and without arbitrarily discarding analysis-worthy data.

Zane Archer Testimonial Headshot
- Zane A., Systems Manager

“We were looking to update our SIEM product but could not justify the cost for a new solution until we found Adlumin. This platform was much easier to deploy than anticipated.”

Adlumin Machine Learning as a Service (MLaaS)

Adlumin’s UEBA can also be leveraged to build Machine Learning as a Service (MLaaS) applications covering a broad array of use cases, complementing the cloud computing resources already available within various F35 development environments by delivering turnkey solutions to numerous forecasting and estimation challenges.

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