Duration
2 Days
12 CPD hours
This course is intended for
Cybersecurity analysts and engineers
Security operations specialists
Overview
Successful completion of this instructor-led course with hands-on lab activities should enable participants to:
Investigate and manage incidents
Describe the Cortex XDR causality and analytics concepts
Analyze alerts using the Causality and Timeline Views
Work with Cortex XDR Pro actions such as remote script execution
Create and manage on-demand and scheduled search queries in the Query Center
Create and manage the Cortex XDR rules BIOC and IOC
Working with Cortex XDR assets and inventories
Write XQL queries to search datasets and visualize the result sets
Work with Cortex XDR's external-data collection
This instructor-led course teaches you how to use the Incidents pages of the Cortex XDR management console to investigate attacks. It explains causality chains, detectors in the Analytics Engine, alerts versus logs, log stitching, and the concepts of causality and analytics. You will learn how to analyze alerts using the Causality and Timeline Views and how to use advanced response actions, such as remediation suggestions, the EDL service, and remote script execution.
Multiple modules focus on how to leverage the collected data. You will create simple search queries in one module and XDR rules in another. The course demonstrate how to use specialized investigation views to visualize artifact-related data, such as IP and Hash Views. Additionally, it provides an introduction to XDR Query Language (XQL). The course concludes with Cortex XDR external-data collection capabilities, including the use of Cortex XDR API to receive external alerts.
This class is powered by Cloud Harmonics.
Course Outline
Module 1 - Cortex XDR Incidents
Module 2 - Causality and Analytics Concepts
Module 3 - Causality Analysis of Alerts
Module 4 - Advanced Response Actions
Module 5 - Building Search Queries
Module 6 - Building XDR Rules
Module 7 - Cortex XDR Assets
Module 8 - Introduction to XQL
Module 9 - External Data Collection