Exabeam Advanced Analytics
The world’s most-deployed UEBA security solution - Modern threat detection using behavioral modeling and machine learning.
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Complex Threat Identification with Behavioral Analysis
Cyberattacks are becoming more complex and harder to find. Often correlation rules can’t find the attacks because they lack context or miss incidents they’ve never seen — generating false negatives. Correlation rules also require significant maintenance. Advanced Analytics, Exabeam’s UEBA security solution, automatically detects the behaviors indicative of a threat. It fully integrates with Exabeam Threat Intelligence Services (TIS) to provide real-time actionable intelligence into potential threats in your environment by uncovering indicators of compromise (IOC) and malicious hosts.
Prebuilt Timelines Automatically Reconstruct Security Incidents
Analysts shouldn’t spend days or weeks gathering evidence and constructing timelines of incidents by querying and pivoting through their SIEM. With Advanced Analytics, a prebuilt-incident timeline flags anomalies and displays details of the incident for the full scope of the event and its context. Now analysts can stop spending time combing through raw logs to investigate incidents. What took weeks to investigate in a legacy SIEM can now be done in seconds with our UEBA security solution.
Extend Behavioral Analytics to Cloud Storage Objects
Organizations are storing their data in the cloud to leverage the scalability, security, and performance of an object storage service. However, cloud data storage has been at the root of many breaches these past few years. That is because configuration blunders can easily expose sensitive data and go undetected by the organization. Exabeam Advanced Analytics logs activity from cloud storage objects in multi-cloud environments namely Amazon S3, Azure Blobs, and Google Cloud Platform Cloud Storage buckets and builds behavioral models to confidently identify malicious user activity from normal user behavior. Exabeam exposes risks inherent to cloud-based data like databases unintentionally exposed to the internet and inappropriate access, providing organizations much needed visibility into their cloud storage object activity to prevent compromising or exfiltration of sensitive data stored in the cloud.
Align Detection to MITRE ATT&CK framework
Inconsistent taxonomy amongst security analysts and security tools complicates collaboration during threat detection and investigation. The MITRE ATT&CK framework solves this problem by providing a common framework analysts can use to describe attacker tactics and techniques. Advanced Analytics maps Exabeam detection methods and event labels to the MITRE ATT&CK framework allowing security analysts to view and filter MITRE techniques within Exabeam Smart Timelines. Analysts can mouse over labels to have a pop-up description of that technique appear, or click on labels to open the MITRE webpage providing a detailed description of that technique.
Customizable Case Management Designed for Security Teams
Managing SOC operations is expensive - it involves organizing resources and prioritizing incidents, in addition to investigating and mitigating those that impact your business. Another pain point is lack of skilled analysts to triage and prioritize incidents. The time required to quickly resolve incidents affects your bottom line. With Exabeam’s UEBA security solution, you can automate these tasks, to decrease mean time to resolution (MTTR), allowing your already stretched security staff to do more in less time. Exabeam Case Manager is fully integrated into Advanced Analytics enabling you to optimize analyst workflow and ensuring that no threats slip through the cracks.
Dynamic Peer Grouping
User behavior patterns often differ based on a myriad of attributes, including: the team they are on, what projects they are involved in, where they are located, and more. Thus, behavioral baselines shouldn’t be static. Dynamic peer grouping uses machine learning to assign users to groups based on their behavior, then to compare their activity against that of those groups to identify anomalous, risky behavior.
Lateral Movement Detection
Lateral movement is a method attackers use to move through a network by using IP addresses, credentials, and machines in search of key assets. Tracking is difficult because the trace information only tells part of the story. Data must be analyzed from everywhere, linking the attack to the source. The Advanced Analytics patented technology tracks suspected activities even if there are changes to devices, IP addresses, or credentials.
Asset Ownership Association
Another time-intensive part of performing a security investigation is the manual process of determining who owns or regularly uses the devices involved in an incident. There isn’t a convenient IT database linking devices to their owners, and mobile devices can exist outside of any tracking. Advanced Analytics is able to determine the owner of a device based on their pattern of behavior and interactions.
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“We were drawn to the fact that out of the box, our security operations analysts can use Exabeam SIEM to respond to alerts without much customization.”