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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	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 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	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 Sample Questions (Q12-Q17):NEW QUESTION # 12
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. clad
• C. pyxd
• 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 # 13
An XDR engineer is creating a correlation rule to monitor login activity on specific systems. When the activity is identified, an alert is created. The alerts are being generated properly but are missing the username when viewed. How can the username information be included in the alerts?

• A. Update the query in the correlation rule to include the username field
• B. Add a drill-down query to the alert which pulls the username field
• C. Select "Initial Access" in the MITRE ATT&CK mapping to include the username
• D. Add a mapping for the username field in the alert fields mapping
  

Answer: D
Explanation:
In Cortex XDR,correlation rulesare used to detect specific patterns or behaviors (e.g., login activity) by analyzing ingested data and generating alerts when conditions are met. For an alert to include specific fields likeusername, the field must be explicitly mapped in thealert fields mappingconfiguration of the correlation rule. This mapping determines which fields from theunderlying dataset are included in the generated alert's details.
In this scenario, the correlation rule is correctly generating alerts for login activity, but theusernamefield is missing. This indicates that the correlation rule's query may be identifying the relevant events, but the usernamefield is not included in the alert's output fields. To resolve this, the engineer must update thealert fields mappingin the correlation rule to explicitly include theusernamefield, ensuring it appears in the alert details when viewed.
* Correct Answer Analysis (C):Adding a mapping for theusernamefield in thealert fields mapping ensures that the field is extracted from the dataset and included in the alert's metadata. This is done in the correlation rule configuration, where administrators can specify which fields to include in the alert output.
* Why not the other options?
* A. Select "Initial Access" in the MITRE ATT&CK mapping to include the username:
Mapping to a MITRE ATT&CK technique like "Initial Access" defines the type of attack or behavior, not specific fields likeusername. This does not address the missing field issue.
* B. Update the query in the correlation rule to include the username field: While the correlation rule's query must reference theusernamefield to detect relevant events, including it in the query alone does not ensure it appears in the alert's output. Thealert fields mappingis still required.
* D. Add a drill-down query to the alert which pulls the username field: Drill-down queries are used for additional investigation after an alert is generated, not for including fields in the alert itself. This does not solve the issue of missingusernamein the alert details.
Exact Extract or Reference:
TheCortex XDR Documentation Portaldescribes correlation rule configuration: "To include specific fields in generated alerts, configure the alert fields mapping in the correlation rule to map dataset fields, such as username, to the alert output" (paraphrased from the Correlation Rules section). TheEDU-262: Cortex XDR Investigation and Responsecourse covers detection engineering, stating that "alert fields mapping determines which data fields are included in alerts generated by correlation rules" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "detection engineering" as a key exam topic, encompassing correlation rule configuration.
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 # 14
An XDR engineer is configuring an automation playbook to respond to high-severity malware alerts by automatically isolating the affected endpoint and notifying the security team via email. The playbook should only trigger for alerts generated by the Cortex XDR analytics engine, not custom BIOCs. Which two conditions should the engineer include in the playbook trigger to meet these requirements? (Choose two.)

• A. Alert category is Malware
• B. Alert status is New
• C. Alert severity is High
• D. Alert source is Cortex XDR Analytics
  

Answer: A,C
Explanation:
In Cortex XDR,automation playbooks(also referred to as response actions or automation rules) allow engineers to define automated responses to specific alerts based on trigger conditions. The playbook in this scenario needs to isolate endpoints and send email notifications for high-severity malware alerts generated by the Cortex XDR analytics engine, excluding custom BIOC alerts. To achieve this, the engineer must configure the playbook trigger with conditions that match the alert's severity, category, and source.
* Correct Answer Analysis (A, C):
* A. Alert severity is High: The playbook should only trigger for high-severity alerts, as specified in the requirement. Setting the conditionAlert severity is Highensures that only alerts with a severity level of "High" activate the playbook, aligning with the engineer's goal.
* C. Alert category is Malware: The playbook targets malware alerts specifically. The condition Alert category is Malwareensures that the playbook only responds to alerts categorized as malware, excluding other types of alerts (e.g., lateral movement, exploit).
* Why not the other options?
* B. Alert source is Cortex XDR Analytics: While this condition would ensure the playbook triggers only for alerts from the Cortex XDR analytics engine (and not custom BIOCs), the requirement to exclude BIOCs is already implicitly met because BIOC alerts are typically categorized differently (e.g., as custom alerts or specific BIOC categories). The alert category (Malware) and severity (High) conditions are sufficient to target analytics-driven malware alerts, and adding the source condition is not strictly necessary for the stated requirements. However, if the engineer wanted to be more explicit, this condition could be considered, but the question asks for the two most critical conditions, which are severity and category.
* D. Alert status is New: The alert status (e.g., New, In Progress, Resolved) determines the investigation stage of the alert, but the requirement does not specify that the playbook should only trigger for new alerts. Alerts with a status of "InProgress" could still be high-severity malware alerts requiring isolation, so this condition is not necessary.
Additional Note on Alert Source: The requirement to exclude custom BIOCs and focus on Cortex XDR analytics alerts is addressed by theAlert category is Malwarecondition, as analytics-driven malware alerts (e.
g., from WildFire or behavioral analytics) are categorized as "Malware," while BIOC alerts are often tagged differently (e.g., as custom rules). If the question emphasized the need to explicitly filter by source, option B would be relevant, but the primary conditions for the playbook are severity and category.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains automation playbook triggers: "Playbook triggers can be configured with conditions such as alert severity (e.g., High) and alert category (e.g., Malware) to automate responses like endpoint isolation and email notifications" (paraphrased from the Automation Rules section).
TheEDU-262: Cortex XDR Investigation and Responsecourse covers playbook creation, stating that
"conditions like alert severity and category ensure playbooks target specific alert types, such as high-severity malware alerts from analytics" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "playbook creation and automation" as a key exam topic, encompassing trigger condition configuration.
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 # 15
A new parsing rule is created, and during testing and verification, all the logs for which field data is to be parsed out are missing. All the other logs from this data source appear as expected. What may be the cause of this behavior?

• A. The Broker VM is offline
• B. The XDR Collector is dropping the logs
• C. The parsing rule corrupted the database
• D. The filter stage is dropping the logs
  

Answer: D
Explanation:
In Cortex XDR,parsing rulesare used to extract and normalize fields from raw log data during ingestion, ensuring that the data is structured for analysis and correlation. The parsing process includes stages such as filtering, parsing, and mapping. If logs for which field data is to be parsed out are missing, while other logs from the same data source are ingested as expected, the issue likely lies within the parsing rule itself, specifically in the filtering stage that determines which logs are processed.
* Correct Answer Analysis (C):The filter stage is dropping the logsis the most likely cause. Parsing rules often include afilter stagethat determines which logs are processed based on specific conditions (e.
g., log content, source, or type). If the filter stage of the new parsing rule is misconfigured (e.g., using an incorrect condition like log_type != expected_type or a regex that doesn't match the logs), it may drop the logs intended for parsing, causing them to be excluded from the ingestion pipeline. Since other logs from the same data source are ingested correctly, the issue is specific to the parsing rule's filter, not a broader ingestion problem.
* Why not the other options?
* A. The Broker VM is offline: If the Broker VM were offline, it would affect all log ingestion from the data source, not just the specific logs targeted by the parsing rule. The question states that other logs from the same data source are ingested as expected, so the Broker VM is likely operational.
* B. The parsing rule corrupted the database: Parsing rules operate on incoming logs during ingestion and do not directly interact with or corrupt the Cortex XDR database. This is an unlikely cause, and database corruption would likely cause broader issues, not just missing specific logs.
* D. The XDR Collector is dropping the logs: The XDR Collector forwards logs to Cortex XDR, and if it were dropping logs, it would likely affect all logs from the data source, not just those targeted by the parsing rule. Since other logs are ingested correctly, the issue is downstream in the parsing rule, not at the collector level.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains parsing rule behavior: "The filter stage in a parsing rule determines which logs are processed; misconfigured filters can drop logs, causing them to be excluded from ingestion" (paraphrased from the Data Ingestion section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers parsing rule troubleshooting, stating that "if specific logs are missing during parsing, check the filter stage for conditions that may be dropping the logs" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "data ingestion and integration" as a key exam topic, encompassing parsing rule configuration and troubleshooting.
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 # 16
When using Kerberos as the authentication method for Pathfinder, which two settings must be validated on the DNS server? (Choose two.)

• A. Reverse DNS zone
• B. AD DS-integrated zones
• C. Reverse DNS records
• D. DNS forwarders
  

Answer: A,C
Explanation:
Pathfinderin Cortex XDR is a tool for discovering unmanaged endpoints in a network, often using authentication methods likeKerberosto access systems securely. Kerberos authentication relies heavily on DNS for resolving hostnames and ensuring proper communication between clients, servers, and the Kerberos Key Distribution Center (KDC). Specific DNS settings must be validated to ensure Kerberos authentication works correctly for Pathfinder.
* Correct Answer Analysis (B, C):
* B. Reverse DNS zone: Areverse DNS zoneis required to map IP addresses to hostnames (PTR records), which Kerberos uses to verify the identity of servers and clients. Without a properly configured reverse DNS zone, Kerberos authentication may fail due to hostname resolution issues.
* C. Reverse DNS records:Reverse DNS records(PTR records) within the reverse DNS zone must be correctly configured for all relevant hosts. These records ensure that IP addresses resolve to the correct hostnames, which is critical for Kerberos to authenticate Pathfinder's access to endpoints.
* Why not the other options?
* A. DNS forwarders: DNS forwarders are used to route DNS queries to external servers when a local DNS server cannot resolve them. While useful for general DNS resolution, they are not specifically required for Kerberos authentication or Pathfinder.
* D. AD DS-integrated zones: Active Directory Domain Services (AD DS)-integrated zones enhance DNS management in AD environments, but they are not strictly required for Kerberos authentication. Kerberos relies on proper forward and reverse DNS resolution, not AD-specific DNS configurations.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains Pathfinder configuration: "For Kerberos authentication, ensure that the DNS server has a properly configured reverse DNS zone and reverse DNS records to support hostname resolution" (paraphrased from the Pathfinder Configuration section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers Pathfinder setup, stating that "Kerberos requires valid reverse DNS zones and PTR records for authentication" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "planning and installation" as a key exam topic, encompassing Pathfinder authentication settings.
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 # 17
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