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CrowdStrike CCSE-204 Exam Syllabus Topics:

SectionWeightObjectives
Data Ingestion20%- 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
- Connector components and management
- Ingestion methods and integration strategies
Parsing20%- Monitoring and resolving parsing errors
- AI-generated parsers and advanced syntax
- Parser testing and validation
- Log format identification and handling
- Parser creation, modification and cloning
- CrowdStrike Parsing Standards and normalization
Content Creation20%- First-party vs third-party detections
- Correlation rules creation, tuning and management
- Dashboard creation and customization
- Content deployment and version control
- Lookup file management and utilization
- CQL query design, building and optimization
Automation and Integration20%- Integration with FalconPy and other tools
- Automated response and remediation
- API access and token management
- External system integration
- Falcon Fusion SOAR workflow design and automation
User Management20%- Multi-factor authentication (MFA) setup
- Repository-level access control
- Role-based access control (RBAC) and built-in roles
- SSO/SAML configuration and claim mapping
- Audit log monitoring and usage
- Custom role creation and permission assignment

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CrowdStrike Certified SIEM Engineer Sample Questions (Q57-Q62):

NEW QUESTION # 57
An event has the following fields:

Which CQL query will output the frequency of a unique set of ComputerName, UserName, CommandLine?

Answer: B

Explanation:
CrowdStrike LogScale documentation states that groupBy() is used to group events by one or more specified fields, similar to SQL GROUP BY. The documentation also says the function parameter accepts aggregate functions, and its default is count(as=_count). That means the query that explicitly groups by ComputerName, UserName, and CommandLine and applies function=count() is the correct way to output the frequency of each unique combination of those three fields.
Why the other options are incorrect:
A is incorrect because table() formats output rows but does not aggregate unique combinations into frequencies the way groupBy() does. Adding count() after table() does not produce grouped counts for each unique triplet. B is incorrect because table() is not the aggregation function documented for grouped frequency counting; groupBy() is. D is close, but it relies on the default count behavior rather than explicitly specifying function=count(). Since the question asks which query will output the frequency of a unique set, C is the most correct and explicit choice.


NEW QUESTION # 58
How does a first-party detection differ from a third-party detection?

Answer: C

Explanation:
The correct answer is D .
CrowdStrike's Falcon Next-Gen SIEM materials distinguish between CrowdStrike detections and third- party detections , and also state that Falcon Next-Gen SIEM extends data collection to third-party data sources . That means first-party detections are native to the Falcon platform, while third-party detections originate from data sources outside the platform that have been onboarded into Next-Gen SIEM.
Why the other options are incorrect:
A is wrong because third-party detections are not defined as detections created by the customer's team.
B is wrong because the distinction is not based on visibility permissions.
C is wrong because CrowdStrike does not define first-party detections as inherently higher severity than third- party detections.


NEW QUESTION # 59
An internal security team identified a small number of high-risk users. They ask you to create an app that will monitor these users and trigger an alert when specific suspicious behavior is detected.
Which Falcon feature should you use to develop this app?

Answer: C

Explanation:
The correct answer is C. Falcon Foundry .
CrowdStrike describes Falcon Foundry as its application development platform for building custom apps on the Falcon platform. CrowdStrike's materials state that Falcon Foundry allows customers to quickly create their own apps, and the Foundry documentation/blog content shows it supports application logic and storage needed for custom workflows and monitoring use cases. That is exactly what fits a requirement to build an app that monitors a defined set of high-risk users and triggers alerts on suspicious activity.
Why the other options are incorrect:
Falcon QueryBuilder is for constructing queries, not building an application. Falcon Spotlight is CrowdStrike's vulnerability management capability, not an app-development framework. Charlotte AI is an AI assistant capability, not the platform feature used to develop custom monitoring apps. The only option that matches "develop this app" is Falcon Foundry .


NEW QUESTION # 60
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: C

Explanation:
Excluding trusted IP addresses helps reduce false positives caused by legitimate user activity while keeping the rule effective at detecting suspicious login patterns from unknown or untrusted sources.


NEW QUESTION # 61
Which CPS-compliant practice should be followed when a third-party field has no matching ECS field?

Answer: A

Explanation:
When a third-party field does not map to ECS, CPS guidance is to preserve it using the Vendor. prefix. This keeps the field searchable and retains source-specific context while maintaining normalization standards.
Removing the field or forcing it into an unrelated ECS field would reduce data quality and clarity.


NEW QUESTION # 62
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