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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: User Management | 20% | - SSO/SAML configuration and claim mapping - Repository-level access control - Role-based access control (RBAC) and built-in roles - Audit log monitoring and usage - Custom role creation and permission assignment - Multi-factor authentication (MFA) setup |
| Topic 2: Content Creation | 20% | - Correlation rules creation, tuning and management - CQL query design, building and optimization - First-party vs third-party detections - Lookup file management and utilization - Dashboard creation and customization - Content deployment and version control |
| Topic 3: Parsing | 20% | - CrowdStrike Parsing Standards and normalization - AI-generated parsers and advanced syntax - Parser testing and validation - Log format identification and handling - Monitoring and resolving parsing errors - Parser creation, modification and cloning |
| Topic 4: Data Ingestion | 20% | - Fleet management and log collector deployment - First-party vs third-party data sources - Built-in and custom data connector configuration - Troubleshooting ingestion and connectivity issues - Ingestion methods and integration strategies - Connector components and management |
| Topic 5: Automation and Integration | 20% | - Integration with FalconPy and other tools - Automated response and remediation - External system integration - Falcon Fusion SOAR workflow design and automation - API access and token management |
>> CCSE-204 Actual Test Answers <<
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NEW QUESTION # 31
Which field should be used in a correlation rule when detections must be based on the original event occurrence time?
Answer: A
Explanation:
@timestamp represents the time the event actually occurred and is the appropriate field for event-time-based detections and correlations. @ingesttimestamp reflects when the platform received the event, which may differ due to delays. @rawstring is raw event content, and @id is not a time field.
NEW QUESTION # 32
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 # 33
While analyzing Falcon data in SIEM, an analyst notices repeated DNS queries to algorithmically generated domain names from a single endpoint.
Answer: D
Explanation:
DGA domains are commonly used by malware for command-and-control.
NEW QUESTION # 34
What dashboard presents a view of third-party data ingestion over the past 30 days?
Answer: D
Explanation:
The correct answer is D. Next-Gen SIEM Connector Dashboard .
CrowdStrike describes the Falcon Next-Gen SIEM Connector Dashboard as the place to understand the status and volume of data ingestion for third-party sources. This matches the question's requirement for a dashboard showing third-party ingestion visibility.
The other options are not aimed at third-party SIEM connector ingestion monitoring:
* Sensor Usage Dashboard relates to Falcon sensor usage, not connector-based third-party ingestion.
* Sensor Subscription Dashboard is about licensing/subscription counts.
* Falcon Flex Dashboard is related to subscription consumption and commercial usage, not connector ingestion telemetry.
NEW QUESTION # 35
You want a consistent view of events from various data sources.
Which ECS field type should you normalize?
Answer: C
Explanation:
Normalizing events to Core Fields in the Elastic Common Schema (ECS) provides a consistent structure across different data sources, enabling reliable search, correlation, and detection in Next-Gen SIEM.
NEW QUESTION # 36
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