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Latest XSIAM-Analyst Exam Practice Questions

The practice questions for XSIAM-Analyst exam was last updated on 2025-09-15 .

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Question#1

Which type of task can be used to create a decision tree in a playbook?

A. Sub-playbook
B. Standard
C. Job
D. Conditional

Explanation:
The correct answer is D C Conditional.
Conditional tasks are used in Cortex XSIAM playbooks to create decision trees. They enable branching logic based on the outcome of previous steps, allowing the playbook to automatically choose different paths and actions depending on analysis results, alert types, or input values.
"Conditional tasks in playbooks enable the construction of decision trees, supporting dynamic response automation based on pre-defined criteria and branching logic."
Document
Reference: XSIAM Analyst ILT Lab Guide.pdf
Page: Page 38 (Automation and Playbooks section)

Question#2

A threat hunter discovers a true negative event from a zero-day exploit that is using privilege escalation to launch "Malware pdf.exe".
Which XQL query will always show the correct user context used to launch "Malware pdf.exe"?

A. config case_sensitive = false | dataset = xdr_data | filter event_type = ENU
B. PROCESS | filter action_process_image_name = "Malware.pdf.exe" | fields causality_actor_effective_username
C. config case_sensitive = false | dataset = xdr_data | filter event_type = ENU
D. PROCESS | filter action_process_image_name = "Malware.pdf.exe" | fields actor_process_username
E. config case_sensitive = false | datamodel dataset = xdrdata | filter xdm.source.process.name = "Malware. pdf.exe" | fields xdm.target.user.username
F. config case_sensitive = false | dataset = xdr_data | filter event_type = ENU
G. PROCESS | filter action_process_image_name = "Malware.pdf.exe" | fields action_process_username

Explanation:
The correct answer is AC the query using the fieldcausality_actor_effective_username.
When analyzing events where privilege escalation is used, it is essential to identify the original effective user that initiated the causality chain, not merely the process’s own running user (as provided by other fields). The fieldcausality_actor_effective_usernamespecifically provides the effective username context of the actor behind the entire chain of actions that resulted in launching the suspicious executable.
Explanation: of fields from Official Document:
causality_actor_effective_username: This field indicates the original effective user who started the entire causality chain.
actor_process_usernameandaction_process_username: These fields indicate the immediate process username, not necessarily reflecting the correct original context when privilege escalation occurs.
Therefore, to always identify the correct user context in privilege escalation scenarios, optionAis the verified correct answer.

Question#3

Which query will hunt for only incoming traffic from 99.99.99.99 when all log sources have been mapped to XDM?

A. datamodel preset = * | filter XD
B. ALIA
C. ip = "99.99.99.99"
D. datamodel dataset = * filter XD
E. ALIA
F. ipv4 = "99.99.99.99"
G. datamodel dataset = * | fields fieldset.xdm_network | filter xdm.source.ipv4 = "99.99.99.99"
H. preset = network_story | filter agent_ip_addresses = "99.99.99.99"

Explanation:
The correct answer is C. This query correctly filters only the incoming traffic from the specific IP address "99.99.99.99":
datamodel dataset = * sets the scope to all XDM-mapped datasets.
fields fieldset.xdm_network explicitly limits the results to network events.
filter xdm.source.ipv4 = "99.99.99.99" specifically targets traffic coming from (incoming) this source IP.
This query adheres to XDM standard data modeling and accurately captures incoming traffic from the specified IP address.
Other provided queries either incorrectly specify fields, presets, or filtering methods.
Therefore, Option Cis the verified, accurate query.

Question#4

Which dataset should an analyst search when looking for Palo Alto Networks NGFW logs?

A. dataset = pan_dss_raw
B. dataset = ngfw
C. dataset = panwngfwtraffic_raw
D. dataset = ngfw_threat_panw_raw

Explanation:
The correct answer is C C dataset = panwngfwtraffic_raw.
The correct dataset for Palo Alto Networks Next-Generation Firewall (NGFW) logs in Cortex XSIAM is panwngfwtraffic_raw, which contains all relevant traffic, threat, and system logs ingested from PAN NGFW devices.
“The panwngfwtraffic_raw dataset contains raw traffic logs collected from Palo Alto Networks NGFW devices and is the recommended source for investigation.”
Document
Reference: EDU-270c-10-lab-guide_02.docx (1).pdf
Page: Page 25 (Data Analysis with XQL section)

Question#5

Which pane in the User Risk View will identify the country from which a user regularly logs in, based on the past few weeks of data?

A. Login Attempts
B. Common Locations
C. Actual Activity
D. Latest Authentication Attempts

Explanation:
The correct answer is B C Common Locations.
The Common Locations pane within the User Risk View provides information about the countries and locations from which a user typically logs in, aggregated from recent weeks of authentication and access data.
"The Common Locations pane in User Risk View displays the countries and regions where the user most frequently logs in, as determined by past weeks of activity."
Document
Reference: XSIAM Analyst ILT Lab Guide.pdf
Page: Page 49 (Dashboards and Reports/User Risk section)

Exam Code: XSIAM-AnalystQ & A: 50 Q&AsUpdated:  2025-09-15

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