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[Hardware] Trustworthy XDR-Engineer Dumps - Test XDR-Engineer Duration

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【Hardware】 Trustworthy XDR-Engineer Dumps - Test XDR-Engineer Duration

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Everything needs a right way. The good method can bring the result with half the effort, the same different exam also needs the good test method. Our XDR-Engineer study materials in every year are summarized based on the test purpose, every answer is a template, there are subjective and objective exams of two parts, we have in the corresponding modules for different topic of deliberate practice. To this end, our XDR-Engineer Study Materials in the qualification exam summarize some problem- solving skills, and induce some generic templates.
Palo Alto Networks XDR-Engineer Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 5
  • 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.

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Palo Alto Networks XDR Engineer Sample Questions (Q34-Q39):NEW QUESTION # 34
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 24 hours
  • C. 24 hours, re-queried to a maximum of 14 days
  • D. 1 hour, re-queried to a maximum of 12 hours
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)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 # 35
Which method will drop undesired logs and reduce the amount of data being ingested?
  • A. [INGEST:vendor="vendor", product="product", target_brokers="vendor_product_raw", no_hit=keep] * filter _raw_log not 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. [COLLECT:vendor="vendor", product="product", target_brokers="", no_hit=drop] * drop _raw_log 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 # 36
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. RULE
  • B. FILTER
  • 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 # 37
Which step is required to configure a proxy for an XDR Collector?
  • A. Configure the proxy settings on the Cortex XDR tenant
  • B. Connect the XDR Collector to the Pathfinder
  • C. Restart the XDR Collector after configuring the proxy settings
  • 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
During deployment of Cortex XDR for Linux Agents, the security engineering team is asked to implement memory monitoring for agent health monitoring. Which agent service should be monitored to fulfill this request?
  • A. dypdng
  • B. pyxd
  • C. clad
  • D. pmd
Answer: D
Explanation:
Cortex XDR agents on Linux consist of several services that handle different aspects of agent functionality, such as event collection, policy enforcement, and health monitoring.Memory monitoringfor agent health involves tracking the memory usage of the agent's core processes to ensure they are operating within acceptable limits, which is critical for maintaining agent stability and performance. Thepmd(Process Monitoring Daemon) service is responsible for monitoring the agent's health, including memory usage, on Linux systems.
* Correct Answer Analysis (D):Thepmdservice should be monitored to fulfill the request for memory monitoring. The Process Monitoring Daemon tracks the Cortex XDR agent's resource usage, including memory consumption, and reports health metrics to the console. Monitoring this service ensures the agent remains healthy and can detect issues like memory leaks or excessive resource usage.
* Why not the other options?
* A. dypdng: This is not a valid Cortex XDR service on Linux. It appears to be a typo or a misnamed service.
* B. clad: The clad service (Cortex Linux Agent Daemon) is responsible for core agent operations, such as communication with the Cortex XDR tenant, but it is not specifically focused on memory monitoring for health purposes.
* C. pyxd: The pyxd service handles Python-based components of the agent, such asscript execution for certain detections, but it is not responsible for memory monitoring or agent health.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains Linux agent services: "The pmd (Process Monitoring Daemon) service on Linux monitors agent health, including memory usage, to ensure stable operation" (paraphrased from the Linux Agent Deployment section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers Linux agent setup, stating that "pmd is the service to monitor for agent health, including memory usage, on Linux systems" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "planning and installation" as a key exam topic, encompassing Linux agent deployment and monitoring.
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
......
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