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| Section | Weight | Objectives |
|---|---|---|
| Log Management and Data Collection | 25% | - Data Sources and Connectors
|
| Dashboards and Reporting | 20% | - Visualization Techniques
|
| Administration and Maintenance | 25% | - System Health Monitoring
|
| Search and Investigation | 30% | - Incident Investigation
|
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NEW QUESTION # 29
You want a consistent view of events from various data sources.
Which ECS field type should you normalize?
Answer: B
Explanation:
Elastic's official ECS guidelines define Core fields as the fields most common across use cases and explicitly state that analysis content built on these fields should work properly on data from any relevant source. They also say to focus on populating these fields first . CrowdStrike's CPS builds on ECS and is intended to standardize field names and structures across different data sources for consistent searching and analysis.
Together, that makes Core fields the right answer when your goal is a consistent cross-source view.
Why the other options are incorrect:
* Extended fields are useful, but ECS defines them as anything not in the core set, so they are not the primary normalization target for broad consistency.
* Base fields and Detection fields are not the correct ECS field-type answer to this question as framed.
NEW QUESTION # 30
Review the log sample below:
What type of parser should be used to extract fields and values from this log?
Answer: B
Explanation:
The sample log is a comma-delimited record with values separated by commas, and some fields are enclosed in quotes. That structure matches CSV-style parsing . In CrowdStrike LogScale, parseCsv() is used for delimited logs where fields appear in a consistent order and are separated by a defined delimiter. This fits the sample shown.
Why the other options are incorrect:
A). XML is incorrect because the log does not use XML tags.
C). JSON is incorrect because the log is not in brace-based key/value JSON format.
D). Key-Value is incorrect because the fields are not expressed as key=value pairs; they are positional comma- separated values instead.
NEW QUESTION # 31
Which role is most appropriate when a user only needs to view SIEM investigations and dashboards but must not modify content?
Answer: B
Explanation:
The least-privilege role for users who only need to view dashboards, searches, and investigation data without making changes is NG SIEM Analyst - Read Only . This role is designed for visibility without content modification or administrative access. The other roles provide broader operational or management permissions.
NEW QUESTION # 32
You are creating an AI-generated parser to process and normalize log data from various sources.
How would you ensure the parser accurately interprets and categorizes the log data?
Answer: A
Explanation:
The correct answer is B . CrowdStrike states that AI-generated parsers are built from sample log records .
Falcon Next-Gen SIEM analyzes those samples to learn the logs' structure and content, so providing representative examples is the documented way to help the parser interpret and categorize data correctly.
Options A and C are not supported by CrowdStrike documentation. There is no requirement for a minimum parser length, and Next-Gen SIEM parsers are not written as Python or Java programs; CrowdStrike's parser template shows a parser schema and script structure specific to Next-Gen SIEM.
NEW QUESTION # 33
Review the log event below:
{"ts": "2018/11/01 14:31:10", "server": "web01", "message": "Out of memory"} Which parsing function is correct to add a missing timezone field?
Answer: B
Explanation:
The correct answer is D . CrowdStrike LogScale's timestamp parsing documentation gives this exact pattern as the example for a JSON event whose ts field contains 2018/11/01 14:31:10 with no timezone present. The documented solution is:
parseJson() | parseTimestamp("yyyy/MM/dd HH:mm:ss", timezone="Europe/Paris", field=ts) This works because the event is JSON, so parseJson() is the right first step, and the timestamp format matches the sample exactly. Since the timestamp string does not include timezone information, CrowdStrike documentation says you must provide a timezone parameter to parseTimestamp().
Why the other options are incorrect:
A is wrong because the format string does not match the timestamp. The event uses 2018/11/01 14:31:10, which is yyyy/MM/dd HH:mm:ss, not dd/MMM/yyyy:HH:mm:ss Z. Also, the sample timestamp does not include a Z timezone token in the raw string. B and C are wrong because kvParse() is for key-value logs, not JSON logs, and this event is clearly JSON. CrowdStrike's built-in parser documentation distinguishes JSON parsing from KV parsing, and the timestamp example for missing timezone specifically uses parseJson() with parseTimestamp().
NEW QUESTION # 34
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