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CrowdStrike CCSE Exam (page: 2)
CrowdStrike Certified SIEM Engineer
Updated on: 31-Mar-2026

Viewing Page 2 of 9
CCSE PDF 60 Questions

You need to ingest data from a custom internal application hosted on-prem. The application writes logs to a file on a syslog server.

Which data connector would you use?

  1. Google Cloud Pub / Sub Data Connector
  2. HTTP Event Connector
  3. Amazon S3 Data Connector
  4. Azure Virtual Machines Data Connector

Answer(s): B

Explanation:

The HTTP Event Connector is used to ingest log data from custom applications, including on-premises sources that can forward logs (such as via a syslog server) over HTTP, enabling integration with Falcon Next- Gen SIEM.



You find a Falcon Log Collector instance on a Linux system that is not connected to Fleet Management.

What command would you use to enroll the Falcon Log Collector?

  1. "C:\Program Files (x86)\CrowdStrike\Humio Log Collector\humio-log- collector.exe" enroll <TOKEN>
  2. sudo logscale-collector enroll <TOKEN>
  3. sudo humio-log-collector enroll <TOKEN>
  4. sudo humio-log-collector --token <TOKEN> enroll

Answer(s): C

Explanation:

On Linux systems, the humio-log-collector enroll <TOKEN> command is used to enroll a Falcon Log Collector into Fleet Management, allowing it to start reporting and receiving configurations.



What is the time format for the @timestamp field when data is parsed using the CrowdStrike Parsing Standard (CPS)?

  1. ISO 8601
  2. Unix Time in microseconds
  3. Human-readable
  4. Unix Time in milliseconds

Answer(s): A

Explanation:

The @timestamp field in CrowdStrike Parsing Standard (CPS) uses the ISO 8601 format, which provides a standardized, human-readable, and timezone-aware representation of date and time for consistent log processing and correlation.



Which CQL statement below includes correct placement of the AND statements and the pipe symbol?

  1. #sourcefile="jobfilename" AND stdout=/\[[\+]\]/ | groupBy([hostname], function=collect([hostname,stdout])) AND stdout != "" AND stdout != "* No artifacts *" | select([hostname,stdout])
  2. #sourcefile="jobfilename" | stdout=/\[[\+]\]/ | groupBy([hostname], function=collect([hostname,stdout])) | stdout != "" AND stdout != "* No artifacts *" AND select([hostname,stdout])
  3. #sourcefile="jobfilename" AND stdout=/\[[\+]\]/ | groupBy([hostname], function=collect([hostname,stdout])) | stdout != "" AND stdout != "* No artifacts *" | select([hostname,stdout])
  4. #sourcefile="jobfilename" | stdout=/\[[\+]\]/ AND groupBy([hostname], function=collect([hostname,stdout])) AND stdout ! = "" | stdout != "* No artifacts *" | select([hostname,stdout])

Answer(s): C

Explanation:

In CQL, filters combined with AND are applied before the pipe (|) operator, which is used to chain functions like groupBy and select. This syntax correctly places the AND conditions for filtering and pipes for processing steps.



A correlation rule is generating a high volume of detections. You have been asked to temporarily deactivate it so your team can investigate.

What will happen to previously generated detections while the rule is in a deactivated state?

  1. They will not be impacted and will remain within the console
  2. Their status will change to closed and tagged as true positives in the console
  3. Their status will change to closed and tagged as false positives in the console
  4. They will be immediately deleted from the console

Answer(s): A

Explanation:

Deactivating a correlation rule stops it from generating new detections but does not affect detections that were already created. Existing detections remain in the console for investigation and tracking.



What is the recommended order of the three required activities to build an efficient CQL query?

  1. Filter > Format > Aggregate
  2. Filter > Aggregate > Format
  3. Format > Filter > Aggregate
  4. Aggregate > Filter > Format

Answer(s): B

Explanation:

The recommended order for building efficient CQL queries is to first filter the data to reduce volume, then aggregate it for analysis, and finally format the results for readability or reporting. This order optimizes performance and clarity.



You have been tasked with parsing the following space delimited log:
2025-06-03 12:13:07 johndoe 192.168.5.15 login

The log source data is guaranteed to always be in the same order.

Which function can parse this log?

  1. parseCEF()
  2. parseJson()
  3. parseCsv()
  4. parseFixedWidth()

Answer(s): C

Explanation:

Even though the log is space-delimited, parseCsv() can parse consistently ordered, delimited data by specifying the delimiter (in this case, a space), making it suitable for structured logs with a fixed field order.



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?

  1. @ingesttimestamp
  2. @rawstring
  3. @error_msg
  4. @event_parsed

Answer(s): D

Explanation:

The @event_parsed metadata field indicates whether an event was successfully parsed during ingestion, allowing engineers to verify parsing success and troubleshoot issues with log data.



Viewing Page 2 of 9



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