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Palo Alto Networks XDR Engineer Sample Questions (Q21-Q26):

NEW QUESTION # 21
When isolating Cortex XDR agent components to troubleshoot for compatibility, which command is used to turn off a component on a Windows machine?

  • A. "C:Program FilesPalo Alto NetworksTrapscytool.exe" occp
  • B. "C:Program FilesPalo Alto NetworksTrapsxdr.exe" stop
  • C. "C:Program FilesPalo Alto NetworksTrapsxdr.exe" -s stop
  • D. "C:Program FilesPalo Alto NetworksTrapscytool.exe" runtime stop

Answer: D

Explanation:
Cortex XDR agents on Windows include multiple components (e.g., for exploit protection, malware scanning, or behavioral analysis) that can be individually enabled or disabled for troubleshooting purposes, such as isolating compatibility issues. Thecytool.exeutility, located in the Cortex XDR installation directory (typically C:Program FilesPalo Alto NetworksTraps), is used to manage agent components and settings. The runtime stop command specifically disables a component without uninstalling the agent.
* Correct Answer Analysis (B):The command"C:Program FilesPalo Alto NetworksTrapscytool.
exe" runtime stopis used to turn off a specific Cortex XDR agent component on a Windows machine.
For example, cytool.exe runtime stop protection would disable the protection component, allowing troubleshooting for compatibility issues while keeping other components active.
* Why not the other options?
* A. "C:Program FilesPalo Alto NetworksTrapsxdr.exe" stop: The xdr.exe binary is not used for managing components; it is part of the agent's corefunctionality. The correct utility is cytool.exe.
* C. "C:Program FilesPalo Alto NetworksTrapsxdr.exe" -s stop: Similarly, xdr.exe is not the correct tool, and -s stop is not a valid command syntax for component management.
* D. "C:Program FilesPalo Alto NetworksTrapscytool.exe" occp: The occp command is not a valid cytool.exe option. The correct command for stopping a component is runtime stop.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains component management: "To disable a Cortex XDR agent component on Windows, use the command cytool.exe runtime stop <component> from the installation directory" (paraphrased from the Troubleshooting section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers agent troubleshooting, stating that "cytool.exe runtime stop is used to turn off specific components for compatibility testing" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "maintenance and troubleshooting" as a key exam topic, encompassing agent component management.
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 # 22
Based on the SBAC scenario image below, when the tenant is switched to permissive mode, which endpoint (s) data will be accessible?

  • A. E1 only
  • B. E1, E2, E3, and E4
  • C. E1, E2, and E3
  • D. E2 only

Answer: C

Explanation:
In Cortex XDR,Scope-Based Access Control (SBAC)restricts user access to data based on predefined scopes, which can be assigned to endpoints, users, or other resources. Inpermissive mode, SBAC allows users to access data within their assigned scopes but may restrict access to data outside those scopes. The question assumes an SBAC scenario with four endpoints (E1, E2, E3, E4), where the user likely has access to a specific scope (e.g., Scope A) that includes E1, E2, and E3, while E4 is in a different scope (e.g., Scope B).
* Correct Answer Analysis (C):When the tenant is switched to permissive mode, the user will have access toE1, E2, and E3because these endpoints are within the user's assigned scope (e.g., Scope A).
E4, being in a different scope (e.g., Scope B), will not be accessible unless the user has explicit accessto that scope. Permissive mode enforces scope restrictions, ensuring that only data within the user's scope is visible.
* Why not the other options?
* A. E1 only: This is too restrictive; the user's scope includes E1, E2, and E3, not just E1.
* B. E2 only: Similarly, this is too restrictive; the user's scope includes E1, E2, and E3, not just E2.
* D. E1, E2, E3, and E4: This would only be correct if the user had access to both Scope A and Scope B or if permissive mode ignored scope restrictions entirely, which it does not. Permissive mode still enforces SBAC rules, limiting access to the user's assigned scopes.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains SBAC: "In permissive mode, Scope-Based Access Control restricts user access to endpoints within their assigned scopes, ensuring data visibility aligns with scope permissions" (paraphrased from the Scope-Based Access Control section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers SBAC configuration, stating that "permissive mode allows access to endpoints within a user's scope, such as E1, E2, and E3, while restricting access to endpoints in other scopes" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheet includes "post-deployment management and configuration" as a key exam topic, encompassing SBAC 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 # 23
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. Monitoring the latest activity of connected firewall endpoints
  • B. Checking for endpoints with outdated agent versions
  • C. Identifying endpoints that have disconnected from the network
  • D. Monitoring the latest activity of endpoints

Answer: D

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 # 24
Which XQL query can be saved as a behavioral indicator of compromise (BIOC) rule, then converted to a custom prevention rule?

  • A. dataset = xdr_data
    | filter event_type = ENUM.DEVICE and action_process_image_name = "**"
    and action_process_image_command_line = "-e cmd*"
    and action_process_image_command_line != "*cmd.exe -a /c*"
  • B. dataset = xdr_data
    | filter event_type = FILE and (event_sub_type = FILE_CREATE_NEW or event_sub_type = FILE_WRITE or event_sub_type = FILE_REMOVE or event_sub_type = FILE_RENAME) and agent_hostname = "hostname"
    | filter lowercase(action_file_path) in ("/etc/*", "/usr/local/share/*", "/usr/share/*") and action_file_extension in ("conf", "txt")
    | fields action_file_name, action_file_path, action_file_type, agent_ip_addresses, agent_hostname, action_file_path
  • C. dataset = xdr_data
    | filter event_type = ENUM.PROCESS and event_type = ENUM.DEVICE and
    action_process_image_name = "**"
    and action_process_image_command_line = "-e cmd*"
    and action_process_image_command_line != "*cmd.exe -a /c*"
  • D. dataset = xdr_data
    | filter event_type = ENUM.PROCESS and action_process_image_name = "**" and action_process_image_command_line = "-e cmd*" and action_process_image_command_line != "*cmd.exe -a /c*"

Answer: D

Explanation:
In Cortex XDR, aBehavioral Indicator of Compromise (BIOC)rule defines a specific pattern of endpoint behavior (e.g., process execution, file operations, or network activity) that can trigger an alert. BIOCs are often created usingXQL (XDR Query Language)queries, which are then saved as BIOC rules to monitor for the specified behavior. To convert a BIOC into acustom prevention rule, the BIOC must be associated with a Restriction profile, which allows the defined behavior to be blocked rather than just detected. For a query to be suitable as a BIOC and convertible to a prevention rule, it must meet the following criteria:
* It must monitor a behavior that Cortex XDR can detect on an endpoint, such as process execution, file operations, or device events.
* The behavior must be actionable for prevention (e.g., blocking a process or file operation), typically involving events like process launches (ENUM.PROCESS) or file modifications (ENUM.FILE).
* The query should not include overly complex logic (e.g., multiple event types with conflicting conditions) that cannot be translated into a BIOC rule.
Let's analyze each query to determine which one meets these criteria:
* Option A: dataset = xdr_data | filter event_type = ENUM.DEVICE ...This query filters for event_type = ENUM.DEVICE, which relates to device-related events (e.g., USB device connections).
While device events can be monitored, the additional conditions (action_process_image_name = "**" and action_process_image_command_line) are process-related attributes, which are typically associated with ENUM.PROCESS events, not ENUM.DEVICE. This mismatch makes the query invalid for a BIOC, as it combines incompatible event types and attributes. Additionally, device events are not typically used for custom prevention rules, as prevention rules focus on blocking processes or fileoperations, not device activities.
* Option B: dataset = xdr_data | filter event_type = ENUM.PROCESS and event_type = ENUM.
DEVICE ...This query attempts to filter for events that are both ENUM.PROCESS and ENUM.
DEVICE (event_type = ENUM.PROCESS and event_type = ENUM.DEVICE), which is logically incorrect because an event cannot have two different event types simultaneously. In XQL, the event_type field must match a single type (e.g., ENUM.PROCESS or ENUM.DEVICE), and combining them with an and operator results in no matches. This makes the query invalid for creating a BIOC rule, as it will not return any results and cannot be used for detection or prevention.
* Option C: dataset = xdr_data | filter event_type = FILE ...This query monitors file-related events (event_type = FILE) with specific sub-types (FILE_CREATE_NEW, FILE_WRITE, FILE_REMOVE, FILE_RENAME) on a specific hostname, targeting file paths (/etc/*, /usr/local/share/*, /usr/share/*) and extensions (conf, txt). While this query can be saved as a BIOC to detect file operations, it is not ideal for conversion to a custom prevention rule. Cortex XDR prevention rules typically focus on blocking process executions (via Restriction profiles), not file operations. While file-based BIOCs can generate alerts, converting them to prevention rules is less common, as Cortex XDR's prevention mechanisms are primarily process-oriented (e.g., terminating a process), not file-oriented (e.g., blocking a file write). Additionally, the query includes complex logic (e.g., multiple sub-types, lowercase() function, fields clause), which may not fully translate to a prevention rule.
* Option D: dataset = xdr_data | filter event_type = ENUM.PROCESS ...This query monitors process execution events (event_type = ENUM.PROCESS) where the process image name matches a pattern (action_process_image_name = "**"), the command line includes -e cmd*, and excludes commands matching *cmd.exe -a /c*. This query is well-suited for a BIOC rule, as it defines a specific process behavior (e.g., a process executing with certain command-line arguments) that Cortex XDR can detect on an endpoint. Additionally, this type of BIOC can be converted to a custom prevention rule by associating it with aRestriction profile, which can block the process execution if the conditions are met. For example, the BIOC can be configured to detect processes with action_process_image_name =
"**" and action_process_image_command_line = "-e cmd*", and a Restriction profile can terminate such processes to prevent the behavior.
Correct Answer Analysis (D):
Option D is the correct choice because it defines a process-based behavior (ENUM.PROCESS) that can be saved as a BIOC rule to detect the specified activity (processes with certain command-line arguments). It can then be converted to a custom prevention rule by adding it to a Restriction profile, which will block the process execution when the conditions are met. The query's conditions are straightforward and compatible with Cortex XDR's BIOC and prevention framework, making it the best fit for the requirement.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains BIOC and prevention rules: "XQL queries monitoring process events (ENUM.PROCESS) can be saved as BIOC rules to detect specific behaviors, and these BIOCs can be added to a Restriction profile to create custom prevention rules that block the behavior" (paraphrased from the BIOC and Restriction Profile sections). TheEDU-260: Cortex XDR Prevention and Deployment course covers BIOC creation, stating that "process-based XQL queries are ideal for BIOCs and can be converted to prevention rules via Restriction profiles to block executions" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "detection engineering" as a key exam topic, encompassing BIOC rule creation and conversion to prevention rules.
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 # 25
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. [COLLECT:vendor="vendor", product="product", target_dataset="", no_hit=drop] * drop _raw_log contains "undesired logs";
  • C. [INGEST:vendor="vendor", product="product", target_dataset="vendor_product_raw",no_hit=drop] * filter _raw_log not 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 # 26
......

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