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Palo Alto Networks XDR Engineer Sample Questions (Q16-Q21):

NEW QUESTION # 16
A correlation rule is created to detect potential insider threats by correlating user login events from one dataset with file access events from another dataset. The rule must retain all user login events, even if there are no matching file access events, to ensure no login activity is missed.
text
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dataset = x
| join (dataset = y)
Which type of join is required to maintain all records from dataset x, even if there are no matching events from dataset y?

• A. Inner
• B. Left
• C. Right
• D. Outer

Answer: B

Explanation:
In Cortex XDR, correlation rules useXQL (XDR Query Language)to combine data from multiple datasets to detect patterns, such as insider threats. Thejoinoperation in XQL is used to correlate events from two datasets based on a common field (e.g., user ID). The type of join determines how records are matched and retained when there are no corresponding events in one of the datasets.
The question specifies that the correlation rule must retainall user login eventsfrom dataset x (the primary dataset containing login events), even if there are no matching file access events in dataset y (the secondary dataset). This requirement aligns with aLeft Join(also called Left Outer Join), which includes all records from the left dataset (dataset x) and any matching records from the right dataset (dataset y). If there is no match in dataset y, the result includes null values for dataset y's fields, ensuring no login events are excluded.
* Correct Answer Analysis (B):ALeft Joinensures that all records from dataset x (user login events) are retained, regardless of whether there are matching file access events in dataset y. This meets the requirement to ensure no login activity is missed.
* Why not the other options?
* A. Inner: An Inner Join only includes records where there is a match in both datasets (x and y).
This would exclude login events from dataset x that have no corresponding file access events in dataset y, which violates the requirement.
* C. Right: A Right Join includes all records from dataset y (file access events) and only matching records from dataset x. This would prioritize file access events, potentially excluding login events with no matches, which is not desired.
* D. Outer: A Full Outer Join includes all records from both datasets, with nulls in places where there is no match. While this retains all login events, it also includes unmatched file access events from dataset y, which is unnecessary for the stated requirement of focusing on login events.
Exact Extract or Reference:
TheCortex XDR Documentation Portalin theXQL Reference Guideexplains join operations: "A Left Join returns all records from the left dataset and matching records from the right dataset. If there is no match, null values are returned for the right dataset's fields" (paraphrased from the XQL Join section). TheEDU-262:
Cortex XDR Investigation and Responsecourse covers correlation rules and XQL, noting that "Left Joins are used in correlation rules to ensure all events from the primary dataset are retained, even without matches in the secondary dataset" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetlists "detection engineering" as a key exam topic, including creating correlation rules with XQL.
References:
Palo Alto Networks Cortex XDR Documentation Portal: XQL Reference Guide (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 # 17
An engineer is building a dashboard to visualize the number of alerts from various sources. One of the widgets from the dashboard is shown in the image below:

The engineer wants to configure a drilldown on this widget to allow dashboard users to select any of the alert names and view those alerts with additional relevant details. The engineer has configured the following XQL query to meet the requirement:
dataset = alerts
| fields alert_name, description, alert_source, severity, original_tags, alert_id, incident_id
| filter alert_name =
| sort desc _time
How will the engineer complete the third line of the query (filter alert_name =) to allow dynamic filtering on a selected alert name?

• A. $x_axis.value
• B. $y_axis.name
• C. $x_axis.name
• D. $y_axis.value

Answer: A

Explanation:
In Cortex XDR, dashboards and widgets supportdrilldownfunctionality, allowing users to click ona widget element (e.g., an alert name in a bar chart) to view detailed data filtered by the selected value. This is achieved usingXQL (XDR Query Language)queries with dynamic variables that reference the clicked element's value. In the provided XQL query, the engineer wants to filter alerts based on thealert_nameselected in the widget.
The widget likely displays alert names along thex-axis(e.g., in a bar chart where each bar represents an alert name and its count). When a user clicks on an alert name, the drilldown query should filter the dataset to show only alerts matching that selectedalert_name. In XQL, dynamic filtering for drilldowns uses variables like $x_axis.value to capture the value of the clicked element on the x-axis.
* Correct Answer Analysis (B):The variable$x_axis.valueis used to reference the value of the x-axis element (in this case, thealert_name) selected by the user. Completing the query with filter alert_name
= $x_axis.value ensures that the drilldown filters the alerts dataset to show only those records where the alert_namematches the clicked value.
* Why not the other options?
* A. $y_axis.value: This variable refers to the value on the y-axis, which typically represents a numerical value (e.g., the count of alerts) in a chart, not the categoricalalert_name.
* C. $x_axis.name: This is not a valid XQL variable for drilldowns. XQL uses $x_axis.value to capture the selected value, not $x_axis.name.
* D. $y_axis.name: This is also not a valid XQL variable, and the y-axis is not relevant for filtering byalert_name.
Exact Extract or Reference:
TheCortex XDR Documentation Portalin theXQL Reference Guideexplains drilldown configuration: "To filter data based on a clicked widget element, use $x_axis.value to reference the value of the x-axis category selected by the user" (paraphrased from the Dashboards and Widgets section). TheEDU-262: Cortex XDR Investigation and Responsecourse covers dashboard creation and XQL, noting that "drilldown queries use variables like $x_axis.value to dynamically filter based on user selections" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetlists "dashboards and reporting" as a key exam topic, including configuring interactive widgets.
References:
Palo Alto Networks Cortex XDR Documentation Portal: XQL Reference Guide (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 # 18
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. INGEST
• C. FILTER
• D. CONST

Answer: D

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 # 19
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. Management Audit Logs
• B. All Endpoints page
• C. XQL query of the endpoints dataset
• D. Asset Inventory

Answer: B,C

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 =
"PARTIALLY_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 # 20
During a recent internal purple team exercise, the following recommendation is given to the detection engineering team: Detect and prevent command line invocation of Python on Windows endpoints by non- technical business units. Which rule type should be implemented?

• A. Analytics Behavioral Indicator of Compromise (ABIOC)
• B. Behavioral Indicator of Compromise (BIOC)
• C. Indicator of Compromise (IOC)
• D. Correlation

Answer: B

Explanation:
The recommendation requires detecting and preventing the command line invocation of Python (e.g., python.
exe or py.exe) on Windows endpoints, specifically for non-technical business units. This involves identifying a specific behavior (command line execution of Python) and enforcing a preventive action (e.g., blocking the process). In Cortex XDR,Behavioral Indicators of Compromise (BIOCs)are used to define and detect specific patterns of behavior on endpoints, such as command line activities, and can be paired with a Restriction profileto block the behavior.
* Correct Answer Analysis (B):ABehavioral Indicator of Compromise (BIOC)rule should be implemented. The BIOC can be configured to detect the command line invocation of Python by defining conditions such as the process name (python.exe or py.exe) and the command line arguments.
For example, a BIOC rule might look for process = python.exe with a command line pattern like cmd.
exe /c python*. This BIOC can then be added to a Restriction profile to prevent the execution of Python by non-technical business units, which can be targeted by applying the profile to specific endpoint groups (e.g., those assigned to non-technical units).
* Why not the other options?
* A. Analytics Behavioral Indicator of Compromise (ABIOC): ABIOCs are analytics-driven rules generated by Cortex XDR's machine learning and behavioralanalytics, not user-defined rules. They are not suitable for creating custom detection and prevention rules like the one needed here.
* C. Correlation: Correlation rules are used to generate alerts by correlating events across multiple datasets (e.g., network and endpoint data), but they do not directly prevent behaviors like command line execution.
* D. Indicator of Compromise (IOC): IOCs are used to detect specific artifacts (e.g., file hashes, IP addresses) associated with known threats, not to detect and prevent behavioral patterns like command line execution.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains BIOC rules: "Behavioral Indicators of Compromise (BIOCs) can detect specific endpoint behaviors, such as command line invocation of processes like Python, and prevent them when added to a Restriction profile" (paraphrased from the BIOC section). TheEDU-260:
Cortex XDR Prevention and Deploymentcourse covers detection engineering, stating that "BIOCs are used to detect and block specific behaviors, such as command line executions, on Windows endpoints" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes
"detection engineering" as a key exam topic, encompassing BIOC rule creation.
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 # 21
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