Better Detection.

Faster Deployment.

Cheaper Tech Spend.

Pick Three.

Security Risk Advisors’ SCALR™ XDR uses a security data lake architecture to minimize SIEM costs, maximize your ability to store security events, and accelerate search and hunting capabilities. The SCALR™ XDR service is enhanced by our distinctive Purple Teams & Defense Success Metrics™.

Operated and Managed 24x7x365

Monitoring & Response by SRA’s skilled team of analysts. We deliver a threat-driven program that proactively identifies needs and works with your team to implement new detections.

SIEM

A turnkey serverless cloud environment with pre-configured and continually-expanding detections.

Data Lake

A modern, scalable and cost-effective data lake model for your security data.

SOAR

Security automation as a first-class feature of your detection and response process.

UEBA

Machine Learning Driven UEBA with no hardware to purchase or deploy.

Purple Teams

Collaborative, open-book testing of your defensive controls.

Continuous Improvement

SCALR™ XDR iterates and improves detections to evolve and stay current with new threats.

SRA identifies new attack TTPs, tests defensive capabilities, and closes visibility gaps through SIEM and EDR engineering.

Purple Teams

Purple teams are the best way to measure the effectiveness of your cyber defenses and drive improvements to your prevention and detection controls. SRA will conduct collaborative red and blue team exercises which will result in quantified and benchmarked measurement over time using our free Purple Teams tool at VECTR.io

Modern Data Pipeline
Management

Log cleansing reduces noise by eliminating unnecessary fields within log files.

Log routing only sends critical events to the SIEM, and the rest are sent to the Data Lake.

Modern Data Pipeline Management cuts down log size and reduces ingest cost.

Reducing Startup
and Technology Costs

SCALR™ XDR can reduce technology spend 50%-75% on average over other cloud or on-premise SIEM. Most clients are in production within 30 days.