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| Section | Weight | Objectives |
|---|---|---|
| Data Ingestion | 20% | - Connector components and management - Troubleshooting ingestion and connectivity issues - Fleet management and log collector deployment - First-party vs third-party data sources - Built-in and custom data connector configuration - Ingestion methods and integration strategies |
| Automation and Integration | 20% | - External system integration - Integration with FalconPy and other tools - Automated response and remediation - Falcon Fusion SOAR workflow design and automation - API access and token management |
| Content Creation | 20% | - First-party vs third-party detections - Dashboard creation and customization - Correlation rules creation, tuning and management - Content deployment and version control - Lookup file management and utilization - CQL query design, building and optimization |
| Parsing | 20% | - Log format identification and handling - Parser testing and validation - Parser creation, modification and cloning - Monitoring and resolving parsing errors - CrowdStrike Parsing Standards and normalization - AI-generated parsers and advanced syntax |
| User Management | 20% | - Role-based access control (RBAC) and built-in roles - Audit log monitoring and usage - SSO/SAML configuration and claim mapping - Multi-factor authentication (MFA) setup - Custom role creation and permission assignment - Repository-level access control |
>> CCSE-204 Exam Guide Materials <<
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NEW QUESTION # 44
A SIEM ingestion pipeline drops events due to high throughput, leading to gaps in visibility during a suspected attack investigation.
Answer: C
Explanation:
Scaling ensures no data loss and complete visibility.
NEW QUESTION # 45
How does a first-party detection differ from a third-party detection?
Answer: C
Explanation:
First-party detections originate from the Falcon platform's own telemetry and analytics, whereas third-party detections are derived from external integrated data sources, such as SIEM logs or other security tools.
NEW QUESTION # 46
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 # 47
An analyst notices that certain critical logs are missing from SIEM during a security incident due to misconfigured log forwarding.
Answer: B
Explanation:
Ensuring proper log ingestion is critical for visibility.
NEW QUESTION # 48
What is the primary benefit of utilizing Next-Gen SIEM's built-in dashboards?
Answer: B
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 # 49
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