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Palo Alto Networks XDR-Engineer Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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.
Topic 5	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.

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Palo Alto Networks XDR Engineer Sample Questions (Q45-Q50):NEW QUESTION # 45
Which method will drop undesired logs and reduce the amount of data being ingested?

• A. [INGEST:vendor="vendor", product="product", target_dataset="vendor_product_raw",no_hit=drop] * filter _raw_log not contains "undesired logs";
• B. [COLLECT:vendor="vendor", product="product", target_dataset="", no_hit=drop] * drop _raw_log contains "undesired logs";
• C. [COLLECT:vendor="vendor", product="product", target_brokers="", no_hit=drop] * drop _raw_log contains "undesired logs";
• D. [INGEST:vendor="vendor", product="product", target_brokers="vendor_product_raw", no_hit=keep] * filter _raw_log not contains "undesired logs";
  

Answer: B
Explanation:
In Cortex XDR, managing data ingestion involves defining rules to collect, filter, or drop logs to optimize storage and processing. The goal is todrop undesired logsto reduce the amount of data ingested. The syntax used in the options appears to be a combination of ingestion rule metadata (e.g., [COLLECT] or [INGEST]) and filtering logic, likely written in a simplified query language for log processing. Thedropaction explicitly discards logs matching a condition, whilefilterwithnot containscan achieve similar results by keeping only logs that do not match the condition.
* Correct Answer Analysis (C):The method in option C,[COLLECT:vendor="vendor", product=" product", target_dataset="", no_hit=drop] * drop _raw_log contains "undesired logs";, explicitly dropslogs where the raw log content contains "undesired logs". The [COLLECT] directive defines the log collection scope (vendor, product, and dataset), and the no_hit=drop parameter indicates that unmatched logs are dropped. The drop _raw_log contains "undesired logs" statement ensures that logs matching the "undesired logs" pattern are discarded, effectively reducing the amount of data ingested.
* Why not the other options?
* A. [COLLECT:vendor="vendor", product="product", target_brokers="", no_hit=drop] * drop _raw_log contains "undesired logs";: This is similar to option C but uses target_brokers="", which is typically used for Broker VM configurations rather than direct dataset ingestion. While it could work, option C is more straightforward with target_dataset="".
* B. [INGEST:vendor="vendor", product="product", target_dataset="
vendor_product_raw", no_hit=drop] * filter _raw_log not contains "undesired logs";: This method uses filter _raw_log not contains "undesired logs" to keep logs that do not match the condition, which indirectly drops undesired logs. However, the drop action in option C is more explicit and efficient for reducing ingestion.
* D. [INGEST:vendor="vendor", product="product", target_brokers="
vendor_product_raw", no_hit=keep] * filter _raw_log not contains "undesired logs";: The no_hit=keep parameter means unmatched logs are kept, which does not align with the goal of reducing data. The filter statement reduces data, but no_hit=keep may counteract this by retaining unmatched logs, making this less effective than option C.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains log ingestion rules: "To reduce data ingestion, use the drop action to discard logs matching specific patterns, such as _raw_log contains 'pattern'" (paraphrased from the Data Ingestion section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers data ingestion optimization, stating that "dropping logs with specific content using drop _raw_log contains is an effective way to reduce ingested data volume" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "data ingestion and integration" as a key exam topic, encompassing log filtering and dropping.
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 # 46
How can a customer ingest additional events from a Windows DHCP server into Cortex XDR with minimal configuration?

• A. Install the Cortex XDR agent
• B. Enable HTTP collector integration
• C. Install the XDR Collector
• D. Activate Windows Event Collector (WEC)
  

Answer: C
Explanation:
To ingest additional events from a Windows DHCP server into Cortex XDR with minimal configuration, the recommended approach is to use theCortex XDR Collector. TheXDR Collectoris a lightweight component designed to collect and forward logs and events from various sources, including Windows servers, to Cortex XDR for analysis and correlation. It is specifically optimized for scenarios where full Cortex XDR agent deployment is not required, and it minimizes configuration overhead by automating much of the data collection process.
For a Windows DHCP server, the XDR Collector can be installed on the server to collect DHCP logs (e.g., lease assignments, renewals, or errors) from the Windows Event Log or other relevant sources. Once installed, the collector forwards these events to the Cortex XDR tenant with minimal setup, requiring only basic configuration such as specifying the target data types and ensuring network connectivity to the Cortex XDR cloud. This approach is more straightforward than alternatives like setting up a full agent or configuring external integrations like Windows Event Collector (WEC) or HTTP collectors, which require additional infrastructure or manual configuration.
* Why not the other options?
* A. Activate Windows Event Collector (WEC): While WEC can collect events from Windows servers, it requires significant configuration, including setting up a WEC server, configuring subscriptions, and integrating with Cortex XDR via a separate ingestion mechanism. This is not minimal configuration.
* C. Enable HTTP collector integration: HTTP collector integration is used for ingesting data via HTTP/HTTPS APIs, which is not applicable for Windows DHCP server events, as DHCP logs are typically stored in the Windows Event Log, not exposed via HTTP.
* D. Install the Cortex XDR agent: The Cortex XDR agent is a full-featured endpoint protection and detection solution that includes prevention, detection, and responsecapabilities. While it can collect some event data, it is overkill for the specific task of ingesting DHCP server events and requires more configuration than the XDR Collector.
Exact Extract or Reference:
TheCortex XDR Documentation Portaldescribes theXDR Collectoras a tool for "collecting logs and events from servers and endpoints with minimal setup" (paraphrased from the Data Ingestion section). TheEDU-260:
Cortex XDR Prevention and Deploymentcourse emphasizes that "XDR Collectors are ideal for ingesting server logs, such as those from Windows DHCP servers, with streamlined configuration" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetlists "data source onboarding and integration configuration" as a key skill, which includes configuring XDR Collectors for log ingestion.
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 # 47
After deploying Cortex XDR agents to a large group of endpoints, some of the endpoints have a partially protected status. In which two places can insights into what is contributing to this status be located? (Choose two.)

• A. Asset Inventory
• B. All Endpoints page
• C. Management Audit Logs
• D. XQL query of the endpoints dataset
  

Answer: B,D
Explanation:
In Cortex XDR, apartially protected statusfor an endpoint indicates that some agent components or protection modules (e.g., malware protection, exploit prevention) are not fully operational, possibly due to compatibility issues, missing prerequisites, or configuration errors. To troubleshoot this status, engineers need to identify the specific components or issues affecting the endpoint, which can be done by examining detailed endpoint data and status information.
* Correct Answer Analysis (B, C):
* B. XQL query of the endpoints dataset: AnXQL (XDR Query Language)query against the endpoints dataset (e.g., dataset = endpoints | filter endpoint_status =
"ARTIALLY_PROTECTED" | fields endpoint_name, protection_status_details) provides detailed insights into the reasons for the partially protected status. The endpoints dataset includes fields like protection_status_details, which specify which modules are not functioning and why.
* C. All Endpoints page: TheAll Endpoints pagein the Cortex XDR console displays a list of all endpoints with their statuses, including those that are partially protected. Clicking into an endpoint's details reveals specific information about the protection status, such as which modules are disabled or encountering issues, helping identify the cause of the status.
* Why not the other options?
* A. Management Audit Logs: Management Audit Logs track administrative actions (e.g., policy changes, agent installations), but they do not provide detailed insights into the endpoint's protection status or the reasons for partial protection.
* D. Asset Inventory: Asset Inventory provides an overview of assets (e.g., hardware, software) but does not specifically detail the protection status of Cortex XDR agents or the reasons for partial protection.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains troubleshooting partially protected endpoints:"Use the All Endpoints page to view detailed protection status, and run an XQL query against the endpoints dataset to identify specific issues contributing to a partially protected status" (paraphrased from the Endpoint Management section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers endpoint troubleshooting, stating that "the All Endpoints page and XQL queries of the endpoints dataset provide insights into partial protection issues" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "maintenance and troubleshooting" as a key exam topic, encompassing endpoint status investigation.
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 # 48
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 14 days
• B. 1 hour, re-queried to a maximum of 12 hours
• C. 24 hours, re-queried to a maximum of 7 days
• D. 1 hour, re-queried to a maximum of 24 hours
  

Answer: C
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)ata 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 # 49
A cloud administrator reports high network bandwidth costs attributed to Cortex XDR operations and asks for bandwidth usage to be optimized without compromising agent functionality. Which two techniques should the engineer implement? (Choose two.)

• A. Enable minor content version updates
• B. Enable agent content management bandwidth control
• C. Configure P2P download sources for agent upgrades and content updates
• D. Deploy a Broker VM and activate the local agent settings applet
  

Answer: B,C
Explanation:
Cortex XDR agents communicate with the cloud for tasks like receiving content updates, agent upgrades, and sending telemetry data, which can consume significant network bandwidth. To optimize bandwidth usage without compromising agent functionality, the engineer should implement techniques that reduce network traffic while maintaining full detection, prevention, and response capabilities.
* Correct Answer Analysis (A, C):
* A. Configure P2P download sources for agent upgrades and content updates: Peer-to-Peer (P2P) download sources allow Cortex XDR agents to share content updates and agent upgrades with other agents on the same network, reducing the need for each agent to download data directly from the cloud. This significantly lowers bandwidth usage, especially in environments with many endpoints.
* C. Enable agent content management bandwidth control: Cortex XDR provides bandwidth control settings in theContent Managementconfiguration, allowing administrators to limit the bandwidth used for content updates and agent communications. This feature throttles data transfers to minimize network impact while ensuring updates are still delivered.
* Why not the other options?
* B. Enable minor content version updates: Enabling minor content version updates ensures agents receive incremental updates, but this alone does not significantly optimize bandwidth, as it does not address the volume or frequency of data transfers. It is a standard practice but not a primary bandwidth optimization technique.
* D. Deploy a Broker VM and activate the local agent settings applet: A Broker VM can act as a local proxy for agent communications, potentially reducing cloud traffic, but thelocal agent settings appletis used for configuring agent settings locally, not for bandwidth optimization.
Additionally, deploying a Broker VM requires significant setup and may not directly address bandwidth for content updates or upgrades compared to P2P or bandwidth control.
Exact Extract or Reference:
TheCortex XDR Documentation Portaldescribes bandwidth optimization: "2P download sources enable agents to share content updates and upgrades locally, reducing cloud bandwidth usage" and "Content Management bandwidth control allows administrators to limit the network impact of agent updates" (paraphrased from the Agent Management and Content Updates sections). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers post-deployment optimization, stating that "2P downloads and bandwidth control settings are key techniques for minimizing network usage" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "post-deployment management and configuration" as a key exam topic, encompassing bandwidth optimization.
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 # 50
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