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| Section | Weight | Objectives |
|---|---|---|
| Log Management and Data Collection | 25% | - Data Sources and Connectors
|
| Administration and Maintenance | 25% | - System Health Monitoring
|
| Search and Investigation | 30% | - Incident Investigation
|
| Dashboards and Reporting | 20% | - Visualization Techniques
|
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NEW QUESTION # 15
When setting up a data connector, which parser can be used to transform incoming data into searchable events that trigger detections in Next-Gen SIEM?
Answer: C
Explanation:
The correct answer is A. CrowdStrike Parsing Standard (CPS) compliant parser .
CrowdStrike's parsing documentation says CPS is used to normalize and validate data so field names and structures are standardized across data sources for more consistent searching and analysis . CPS-compliant parsers also require specific tags and field population rules, which is exactly what makes incoming data searchable and detection-ready in Falcon Next-Gen SIEM.
The other options are not the general standard CrowdStrike uses for detection-ready normalization:
* Charlotte AI-generated parser is not the documented parser standard.
* VMWare ESXI parser and Linux syslog parser may describe source-specific parsers, but the question asks for the parser type used generally to transform incoming data into normalized, searchable events. That is CPS.
NEW QUESTION # 16
As a Next-Gen SIEM Engineer, you are responsible for managing and tuning correlation rules to improve the detection of potential security incidents. One of your correlation rules is designed to detect multiple failed login attempts that are followed by a successful login within a short time frame.
Which step would you take to tune this correlation rule to reduce false positives while maintaining its effectiveness?
Answer: B
Explanation:
The correct answer is B . The best tuning step is to exclude known trusted IP addresses so the rule still detects suspicious sequences while removing known-benign sources of repeated authentication activity.
CrowdStrike has publicly documented this tuning principle in detection content guidance, noting that to avoid false positives, organizations may want to exclude certain IP ranges, ASNs, or ISPs from a rule when those sources are expected or trusted. That directly supports the idea that adding a trusted-IP exclusion reduces noise while preserving the core detection logic.
Why the other options are incorrect:
A would usually increase noise because a larger time window captures more benign failed logins. C would also increase false positives because lowering the failed-attempt threshold makes the rule easier to trigger. D weakens the original attack logic by removing the "failed logins followed by success" sequence that makes the rule more specific and meaningful. Keeping the core sequence intact while adding exclusions for known benign sources is the most precise tuning approach.
NEW QUESTION # 17
What is the primary benefit of utilizing Next-Gen SIEM's built-in dashboards?
Answer: A
Explanation:
The correct answer is C. Quick insights without manual setup .
CrowdStrike describes Falcon Next-Gen SIEM as providing pre-built dashboards and says teams can quickly understand security and system health with prebuilt dashboards for data collection health, SOAR workflow executions, security trends, and more. That directly supports the idea that the main benefit is getting fast visibility and insights without having to build everything manually first .
Why the other options are incorrect:
A is incorrect because dashboards are for visualization and insight, not primarily for raw log access. B is incorrect because custom queries are a separate search capability, not the main value proposition of built-in dashboards. D is incorrect because CrowdStrike emphasizes using pre-built and custom dashboards for visualization, not modifying dashboard source code as the primary benefit.
NEW QUESTION # 18
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: C
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 # 19
When deploying the Falcon Log Collector using the commands in the CrowdStrike Fleet Management interface, what is the correct service name?
Answer: C
Explanation:
The Falcon Log Collector service is named logscale-collector, which is used in installation, enrollment, and management commands when deploying via the CrowdStrike Fleet Management interface.
NEW QUESTION # 20
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