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[General] Free PDF Quiz 2026 High Hit-Rate Palo Alto Networks Cert XDR-Engineer Guide

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【General】 Free PDF Quiz 2026 High Hit-Rate Palo Alto Networks Cert XDR-Engineer Guide

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Palo Alto Networks XDR Engineer Sample Questions (Q37-Q42):NEW QUESTION # 37
Which step is required to configure a proxy for an XDR Collector?
  • A. Configure the proxy settings on the Cortex XDR tenant
  • B. Restart the XDR Collector after configuring the proxy settings
  • C. Connect the XDR Collector to the Pathfinder
  • D. Edit the YAML configuration file with the new proxy information
Answer: D
Explanation:
TheXDR Collectorin Cortex XDR is a lightweight tool for collecting logs and events from servers and endpoints. When a proxy is required for the XDR Collector to communicate with the Cortex XDR cloud, the proxy settings must be configured in the collector's configuration file. Specifically, theYAML configuration file(e.g., config.yaml) must be edited to include the proxy details, such as the proxy server's address, port, and authentication credentials (if required).
* Correct Answer Analysis (A):To configure a proxy for the XDR Collector, the engineer mustedit the YAML configuration filewith the new proxy information. This involves adding or updating the proxy settings in the file, which the collector uses to route its traffic through the specified proxy server.
* Why not the other options?
* B. Restart the XDR Collector after configuring the proxy settings: While restarting the collector may be necessary to apply changes, it is not the primary step required to configure the proxy. The YAML file must be edited first.
* C. Connect the XDR Collector to the Pathfinder: The Pathfinder is a Cortex XDR feature for discovering endpoints, not for configuring proxy settings for the XDR Collector.
* D. Configure the proxy settings on the Cortex XDR tenant: Proxy settings for the XDR Collector are configured locally on the collector, not in the Cortex XDR tenant's web interface.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains XDR Collector configuration: "To configure a proxy for the XDR Collector, edit the YAML configuration file to include the proxy server details, such as address and port" (paraphrased from the XDR Collector Configuration section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers XDR Collector setup, stating that"proxy settings are configured by editing the collector's YAML file" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "data ingestion and integration" as a key exam topic, encompassing XDR Collector configuration.
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 # 38
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. Deploy a Broker VM and activate the local agent settings applet
  • B. Enable agent content management bandwidth control
  • C. Enable minor content version updates
  • D. Configure P2P download sources for agent upgrades and content updates
Answer: B,D
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 # 39
Which action is being taken with the query below?
dataset = xdr_data
| fields agent_hostname, _time, _product
| comp latest as latest_time by agent_hostname, _product
| join type=inner (dataset = endpoints
| fields endpoint_name, endpoint_status, endpoint_type) as lookup lookup.endpoint_name = agent_hostname
| filter endpoint_status = ENUM.CONNECTED
| fields agent_hostname, endpoint_status, latest_time, _product
  • A. Identifying endpoints that have disconnected from the network
  • B. Checking for endpoints with outdated agent versions
  • C. Monitoring the latest activity of endpoints
  • D. Monitoring the latest activity of connected firewall endpoints
Answer: C
Explanation:
The providedXQL (XDR Query Language)query in Cortex XDR retrieves and processes data to provide insights into endpoint activity. Let's break down the query to understand its purpose:
* dataset = xdr_data | fields agent_hostname, _time, _product: Selects thexdr_datadataset (general event data) and retrieves fields for the agent hostname, timestamp, and product (e.g., agent type or component).
* comp latest as latest_time by agent_hostname, _product: Computes the latest timestamp (_time) for each combination of agent_hostname and _product, naming the result latest_time. This identifies the most recent activity for each endpoint and product.
* join type=inner (dataset = endpoints | fields endpoint_name, endpoint_status, endpoint_type) as lookup lookup.endpoint_name = agent_hostname: Performs an inner join with theendpointsdataset, matching endpoint_name (from the endpoints dataset) with agent_hostname (from xdr_data), and retrieves fields like endpoint_status and endpoint_type.
* filter endpoint_status = ENUM.CONNECTED: Filters the results to include only endpoints with a status ofCONNECTED.
* fields agent_hostname, endpoint_status, latest_time, _product: Outputs the final fields: hostname, status, latest activity time, and product.
* Correct Answer Analysis (A):The query ismonitoring the latest activity of endpoints. It calculates the most recent activity (latest_time) for each connected endpoint (agent_hostname) by joining event data (xdr_data) with endpoint metadata (endpoints) and filtering for connected endpoints. This provides a view of the latest activity for active endpoints, useful for monitoring their status and recent events.
* Why not the other options?
* B. Identifying endpoints that have disconnected from the network: The queryfilters for endpoint_status = ENUM.CONNECTED, so it only includes connected endpoints, not disconnected ones.
* C. Monitoring the latest activity of connected firewall endpoints: The query does not filter for firewall endpoints (e.g., using endpoint_type or _product to specify firewalls). It applies to all connected endpoints, not just firewalls.
* D. Checking for endpoints with outdated agent versions: The query does not retrieve or compare agent version information (e.g., agent_version field); it focuses on the latest activity time.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains XQL queries: "Queries using comp latest and joins with the endpoints dataset can monitor the latest activity of connected endpoints by calculating the most recent event timestamps" (paraphrased from the XQL Reference Guide). TheEDU-262: Cortex XDR Investigation and Responsecourse covers XQL for monitoring, stating that "combining xdr_data and endpoints datasets with a latest computation monitors recent endpoint activity" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "dashboards and reporting" as a key exam topic, encompassing XQL queries for monitoring.
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 # 40
Log events from a previously deployed Windows XDR Collector agent are no longer being observed in the console after an OS upgrade. Which aspect of the log events is the probable cause of this behavior?
  • A. They are in Filebeat format
  • B. They are in Winlogbeat format
  • C. They are less than 1MB
  • D. They are greater than 5MB
Answer: D

NEW QUESTION # 41
Which method will drop undesired logs and reduce the amount of data being ingested?
  • A. [COLLECT:vendor="vendor", product="product", target_brokers="", no_hit=drop] * drop _raw_log contains "undesired logs";
  • B. [INGEST:vendor="vendor", product="product", target_dataset="vendor_product_raw",no_hit=drop] * filter _raw_log not contains "undesired logs";
  • C. [COLLECT:vendor="vendor", product="product", target_dataset="", 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: C
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 # 42
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