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CrowdStrike CCSE-204 Exam Syllabus Topics:

SectionObjectives
Topic 1: Exam domains (official detailed syllabus not publicly disclosed)- CrowdStrike SIEM and log analysis fundamentals
- Threat detection and incident investigation workflows in CrowdStrike platform
- Dashboards, reporting, and alerting configuration
- Security event ingestion, normalization, and correlation concepts
- Operational use of CrowdStrike Falcon modules for SIEM engineering tasks

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CrowdStrike Certified SIEM Engineer Sample Questions (Q44-Q49):

NEW QUESTION # 44
You are onboarding a log source that includes a timestamp with a different timezone.
How should you address any time parsing errors that occur?

Answer: C

Explanation:
The correct answer is A . CrowdStrike documentation states that when a timestamp does not include timezone information, or when you need to control timezone interpretation, you should pass the timezone parameter to parseTimestamp() or findTimestamp(). Since parsers are where ingest-time transformations are defined, the correct engineering approach is to create or clone a custom parser for that log source and explicitly apply the needed timezone handling there. CrowdStrike's custom parser docs explain that parsers are used to control how incoming events are transformed during ingest, and the timestamp parsing docs explain that timezone can be set directly in the parser logic.
Why the other options are incorrect:
B is not the documented parser-side solution. While changing the source may work operationally in some environments, CrowdStrike's parsing guidance focuses on fixing time interpretation in the parser by using timezone or related timestamp parsing controls. C is incorrect because changing the timestamp field name does not solve timezone parsing. D is incorrect because dropping the source timestamp and relying on ingest time would lose the original event time, which is exactly what parsers are meant to preserve by converting source timestamps into @timestamp. CrowdStrike explicitly states that one of the most important jobs of a parser is assigning correct timestamps to events.


NEW QUESTION # 45
You are onboarding a log source that includes a timestamp with a different timezone.
How should you address any time parsing errors that occur?

Answer: C

Explanation:
When logs have timestamps in a different timezone, cloning the parser and specifying the correct timezone parameter in the parseTimestamp() function ensures accurate time parsing without altering field names or losing data.


NEW QUESTION # 46
You are reviewing a lookup file to determine whether an event was successfully parsed during ingestion.
Which metadata field indicates the event's parsing status?

Answer: B

Explanation:
The correct answer is D. @event_parsed .
CrowdStrike LogScale's parser error documentation explicitly states that @event_parsed indicates whether the event has been successfully parsed during ingest . The same documentation says it is set to false when there was a parsing error. That exactly matches the question.
Why the other options are incorrect:
@ingesttimestamp represents the time the platform ingested the event, not whether parsing succeeded.
@rawstring contains the original raw event data. @error_msg can contain error details, but it is not the primary field that directly indicates parse success or failure. The field CrowdStrike documents for parsing status is @event_parsed .


NEW QUESTION # 47
Which CQL statement below includes correct placement of the AND statements and the pipe symbol?

Answer: C

Explanation:
The correct answer is C . In CQL, boolean conditions such as AND belong inside filter expressions, while pipeline functions like groupBy() and select() must be separated with the pipe (|) operator. CrowdStrike syntax guidance shows that functions are chained through the pipeline and should not be combined with AND. Option C correctly uses AND for the filter logic and uses pipes to separate the aggregation and projection steps.


NEW QUESTION # 48
An event has the following fields:

Which CQL query will output the frequency of a unique set of ComputerName, UserName, CommandLine?
#event_simpleName = ProcessRollup2 FileName = ssh.exe CommandLine = /\s-

Answer: D

Explanation:
Using groupBy() with function=count() aggregates the events by the unique combination of ComputerName, UserName, and CommandLine, producing the frequency of each unique set.
This approach correctly handles the CQL syntax for counting occurrences.


NEW QUESTION # 49
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