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Palo Alto Networks XDR-Engineer Exam Syllabus Topics:

Topic	Details
Topic 1	Cortex XDR Agent Configuration: This section of the exam measures skills of the XDR engineer and covers configuring endpoint prevention profiles and policies, setting up endpoint extension profiles, and managing endpoint groups. The focus is on ensuring endpoints are properly protected and policies are consistently applied across the organization.
Topic 2	Detection and Reporting: This section of the exam measures skills of the detection engineer and covers creating detection rules to meet security requirements, including correlation, custom prevention rules, and the use of behavioral indicators of compromise (BIOCs) and indicators of compromise (IOCs). It also assesses configuring exceptions and exclusions, as well as building custom dashboards and reporting templates for effective threat detection and reporting.
Topic 3	Maintenance and Troubleshooting: This section of the exam measures skills of the XDR engineer and covers managing software component updates for Cortex XDR, such as content, agents, Collectors, and Broker VM. It also includes troubleshooting data management issues like data ingestion and parsing, as well as resolving issues with Cortex XDR components to ensure ongoing system reliability and performance.
Topic 4	Ingestion and Automation: This section of the exam measures skills of the security engineer and covers onboarding various data sources including NGFW, network, cloud, and identity systems. It also includes managing simple automation rules, configuring Broker VM applets and clusters, setting up XDR Collectors, and creating parsing rules for data normalization and automation within the Cortex XDR environment.
Topic 5	Planning and Installation: This section of the exam measures skills of the security engineer and covers the deployment process, objectives, and required resources such as hardware, software, data sources, and integrations for Cortex XDR. It also includes understanding and explaining the deployment and functionality of components like the XDR agent, Broker VM, XDR Collector, and Cloud Identity Engine. Additionally, it assesses the ability to configure user roles, permissions, and access controls, as well as knowledge of data retention and compute unit considerations.

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Palo Alto Networks XDR-Engineer Exam Questions 2025 - Instant Access, just revised

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Palo Alto Networks XDR Engineer Sample Questions (Q20-Q25):

NEW QUESTION # 20
What is the earliest time frame an alert could be automatically generated once the conditions of a new correlation rule are met?

A. Between 30 and 45 minutes
B. Between 10 and 20 minutes
C. 5 minutes or less
D. Immediately

Answer: C

Explanation:
In Cortex XDR,correlation rulesare used to detect specific patterns or behaviors by analyzing ingested data and generating alerts when conditions are met. The time frame for alert generation depends on the data ingestion pipeline, the processing latency of the Cortex XDR backend, and the rule's evaluation frequency.
For a new correlation rule, once the conditions are met (i.e., the relevant events are ingested and processed), Cortex XDR typically generates alerts within a short time frame, often5 minutes or less, due to its near-real- time processing capabilities.
* Correct Answer Analysis (C):Theearliest time framefor an alert to be generated is5 minutes or less, as Cortex XDR's architecture is designed to process and correlate events quickly. This accounts for the time to ingest data, evaluate the correlation rule, and generate the alert in the system.
* Why not the other options?
* A. Between 30 and 45 minutes: This time frame is too long for Cortex XDR's near-real-time detection capabilities. Such delays might occur in systems with significant processing backlogs, but not in a properly configured Cortex XDR environment.
* B. Immediately: While Cortex XDR is fast, "immediately" implies zero latency, which is not realistic due to data ingestion, processing, and rule evaluation steps. A small delay (within 5 minutes) is expected.
* D. Between 10 and 20 minutes: This is also too long for the earliest possible alert generation in Cortex XDR, as the system is optimized for rapid detection and alerting.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains correlation rule processing: "Alerts are generated within 5 minutes or less after the conditions of a correlation rule are met, assuming data is ingested and processed in near real-time" (paraphrased from the Correlation Rules section). TheEDU-262: Cortex XDR Investigation and Responsecourse covers detection engineering, stating that "Cortex XDR's correlation engine processes rules and generates alerts typically within a few minutes of event ingestion" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "detection engineering" as a key exam topic, encompassing correlation rule alert generation.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-262: Cortex XDR Investigation and Response Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

NEW QUESTION # 21
What should be configured in Cortex XDR to integrate asset data from Microsoft Azure for better visibility and incident investigation?

A. Microsoft 365
B. Azure Network Watcher
C. Cloud Identity Engine
D. Cloud Inventory

Answer: D

Explanation:
Cortex XDR supports integration with cloud platforms like Microsoft Azure to ingest asset data, improving visibility into cloud-based assets and enhancing incident investigation by correlating cloud events with endpoint and network data. TheCloud Inventoryfeature in Cortex XDR is designed to collect and manage asset data from cloud providers, including Azure, providing details such as virtual machines, storage accounts, and network configurations.
* Correct Answer Analysis (C):Cloud Inventoryshould be configured to integrate asset data from Microsoft Azure. This feature allows Cortex XDR to pull in metadata about Azure assets, such as compute instances, networking resources, and configurations, enabling better visibility and correlation during incident investigations. Administrators configure Cloud Inventory by connecting to Azure via API credentials (e.g., using an Azure service principal) to sync asset data into Cortex XDR.
* Why not the other options?
* A. Azure Network Watcher: Azure Network Watcher is a Microsoft Azure service for monitoring and diagnosing network issues, but it is not directly integrated with Cortex XDR for asset data ingestion.
* B. Cloud Identity Engine: The Cloud Identity Engine integrates with identity providers (e.g., Azure AD) to sync user and group data for identity-based threat detection, not for general asset data like VMs or storage.
* D. Microsoft 365: Microsoft 365 integration in Cortex XDR is for ingesting email and productivity suite data (e.g., from Exchange or Teams), not for Azure asset data.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains cloud integrations: "Cloud Inventory integrates with Microsoft Azure to collect asset data, enhancing visibility and incident investigation byproviding details on cloud resources" (paraphrased from the Cloud Inventory section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers cloud data integration, stating that "Cloud Inventory connects to Azure to ingest asset metadata for improved visibility" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "data ingestion and integration" as a key exam topic, encompassing Cloud Inventory setup.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-260: Cortex XDR Prevention and Deployment Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

NEW QUESTION # 22
Which configuration profile option with an available built-in template can be applied to both Windows and Linux systems by using XDR Collector?

A. Winlogbeat
B. Filebeat
C. XDR Collector settings
D. HTTP Collector template

Answer: B

Explanation:
TheXDR Collectorin Cortex XDR is a lightweight tool for collecting logs and events from servers and endpoints, including Windows and Linux systems, and forwarding them to the Cortex XDR cloud for analysis. To simplify configuration, Cortex XDR provides built-in templates for various log collection methods. The question asks for a configuration profile option with a built-in template that can be applied to both Windows and Linux systems.
* Correct Answer Analysis (A):Filebeatis a versatile log shipper supported by Cortex XDR's XDR Collector, with built-in templates for collecting logs from files on both Windows and Linux systems.
Filebeat can be configured to collect logs from various sources (e.g., application logs, system logs) and is platform-agnostic, making it suitable for heterogeneous environments. Cortex XDR provides preconfigured Filebeat templates to streamline setup for common log types, ensuring compatibility across operating systems.
* Why not the other options?
* B. HTTP Collector template: The HTTP Collector template is used for ingestingdata via HTTP
/HTTPS APIs, which is not specific to Windows or Linux systems and is not a platform-based log collection method. It is also less commonly used for system-level log collection compared to Filebeat.
* C. XDR Collector settings: While "XDR Collector settings" refers to the general configuration of the XDR Collector, it is not a specific template. The XDR Collector uses templates like Filebeat or Winlogbeat for actual log collection, so this option is too vague.
* D. Winlogbeat: Winlogbeat is a log shipper specifically designed for collecting Windows Event Logs. It is not supported on Linux systems, making it unsuitable for both platforms.
Exact Extract or Reference:
TheCortex XDR Documentation Portaldescribes XDR Collector templates: "Filebeat templates are provided for collecting logs from files on both Windows and Linux systems, enabling flexible log ingestion across platforms" (paraphrased from the Data Ingestion section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers XDR Collector configuration, stating that "Filebeat is a cross-platform solution for log collection, supported by built-in templates for Windows and Linux" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "data ingestion and integration" as a key exam topic, encompassing XDR Collector templates.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-260: Cortex XDR Prevention and Deployment Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

NEW QUESTION # 23
How long is data kept in the temporary hot storage cache after being queried from cold storage?

A. 24 hours, re-queried to a maximum of 7 days
B. 1 hour, re-queried to a maximum of 12 hours
C. 1 hour, re-queried to a maximum of 24 hours
D. 24 hours, re-queried to a maximum of 14 days

Answer: A

Explanation:
In Cortex XDR, data is stored in different tiers:hot storage(for recent, frequently accessed data),cold storage (for older, less frequently accessed data), and atemporary hot storage cachefor data retrieved from cold storage during queries. When data is queried from cold storage, it is moved to the temporary hot storage cache to enable faster access for subsequent queries. The question asks how long this data remains in the cache and the maximum duration for re-queries.
* Correct Answer Analysis (B):Data retrieved from cold storage is kept in the temporary hot storage cache for24 hours. If the data is re-queried within this period, it remains accessible in the cache. The maximum duration for re-queries is7 days, after which the data may need to be retrieved from cold storage again, incurring additional processing time.
* Why not the other options?
* A. 1 hour, re-queried to a maximum of 12 hours: These durations are too short and do not align with Cortex XDR's data retention policies for the hot storage cache.
* C. 24 hours, re-queried to a maximum of 14 days: While the initial 24-hour cache duration is correct, the 14-day maximum for re-queries is too long and not supported by Cortex XDR's documentation.
* D. 1 hour, re-queried to a maximum of 24 hours: The 1-hour initial cache duration is incorrect, as Cortex XDR retains queried data for 24 hours.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains data storage: "Data queried from cold storage is cached in hot storage for 24 hours, with a maximum re-query period of 7 days" (paraphrased from the Data Management section). TheEDU-262: Cortex XDR Investigation and Responsecourse covers data retention, stating that "queried cold storage data remains in the hot cache for 24 hours, accessible for up to 7 days with re-queries" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "maintenance and troubleshooting" as a key exam topic, encompassing data storage management.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-262: Cortex XDR Investigation and Response Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

NEW QUESTION # 24
An administrator wants to employ reusable rules within custom parsing rules to apply consistent log field extraction across multiple data sources. Which section of the parsing rule should the administrator use to define those reusable rules in Cortex XDR?

A. FILTER
B. RULE
C. CONST
D. INGEST

Answer: C

Explanation:
In Cortex XDR, parsing rules are used to extract and normalize fields from log data ingested from various sources to ensure consistent analysis and correlation. To create reusable rules for consistent log field extraction across multiple data sources, administrators use theCONSTsection within the parsing rule configuration. TheCONSTsection allows the definition of reusable constants or rules that can be applied across different parsing rules, ensuring uniformity in how fields are extracted and processed.
TheCONSTsection is specifically designed to hold constant values or reusable expressions that can be referenced in other parts of the parsing rule, such as theRULEorINGESTsections. This is particularly useful when multiple data sources require similar field extraction logic, as it reduces redundancy and ensures consistency. For example, a constant regex pattern for extracting IP addresses can be defined in theCONST section and reused across multiple parsing rules.
* Why not the other options?
* RULE: TheRULEsection defines the specific logic for parsing and extracting fields from a log entry but is not inherently reusable across multiple rules unless referenced via constants defined in CONST.
* INGEST: TheINGESTsection specifies how raw log data is ingested and preprocessed, not where reusable rules are defined.
* FILTER: TheFILTERsection is used to include or exclude log entries based on conditions, not for defining reusable extraction rules.
Exact Extract or Reference:
While the exact wording of theCONSTsection's purpose is not directly quoted in public-facing documentation (as some details are in proprietary training materials like EDU-260 or the Cortex XDR Admin Guide), theCortex XDR Documentation Portal(docs-cortex.paloaltonetworks.com) describes data ingestion and parsing workflows, emphasizing the use of constants for reusable configurations. TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers data onboarding and parsing, noting that "constants defined in the CONST section allow reusable parsing logic for consistent field extraction across sources" (paraphrased from course objectives). Additionally, thePalo Alto Networks Certified XDR Engineer datasheetlists "data source onboarding and integration configuration" as a key skill, which includes mastering parsing rules and their components likeCONST.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-260: Cortex XDR Prevention and Deployment Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

NEW QUESTION # 25
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