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Splunk SPLK-5003 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Security Capability Selection, Placement, and Configuration	15%	- Evaluating and selecting security technologies - Architectural placement and integration design - Optimization and tuning of security components
Topic 2: Security Data Management	20%	- Enterprise-scale data ingestion and normalization - Schema design and Common Information Model (CIM) implementation - Data retention, storage, and archiving strategies - Data quality, validation, and governance
Topic 3: Governance, Risk and Compliance	10%	- Risk assessment and management frameworks - Aligning security with regulatory requirements - Policy development and enforcement
Topic 4: Measuring and Improving Security Program Effectiveness	15%	- Security metrics and KPIs design - Continuous monitoring and improvement processes - Maturity models and capability assessments
Topic 5: Scaling Cybersecurity Defenses and DevSecOps	15%	- Distributed and high-availability security deployments - Cloud and hybrid environment security design - Security in software development lifecycle
Topic 6: Advanced Threat Intelligence and Analysis	5%	- Threat intelligence lifecycle management - Advanced threat hunting methodologies - Integrating threat data into security architecture
Topic 7: Advanced Automation and Orchestration	10%	- Automation strategy and governance - Integration with enterprise systems and tools - Designing scalable SOAR architectures
Topic 8: Advanced Incident Response and Management	10%	- Designing incident response frameworks - Orchestrated response workflows - Post-incident activities and continuous improvement

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Splunk Certified Cybersecurity Defense Architect Sample Questions (Q17-Q22):

NEW QUESTION # 17
The growing rate of cyber attacks has led many countries to adopt laws and regulations pertaining to the collection, handling, and security of their citizens' private information regardless of where it is stored. Which of the following terms best describes these laws?

A. Data shielding
B. Data sovereignty
C. Data residency
D. Data providence

Answer: B

Explanation:
Data sovereignty means data is subject to the laws and governance requirements of the country whose citizens or residents the data relates to, regardless of where that data is stored or processed. This affects architecture decisions for privacy, compliance, access controls, and cross-border data handling.

NEW QUESTION # 18
Which of the following are valid reasons to implement index-time field extraction instead of search-time extraction? (Choose all that apply.)

A. Simplifies future field renaming
B. Improves data onboarding flexibility
C. Necessary for fields used heavily in tstats-based searches
D. Reduces search-time CPU overhead for frequently searched fields

Answer: C,D

Explanation:
Index-time extraction improves performance for fields that are searched very frequently or required by tstats (which relies on indexed fields), at the cost of flexibility, since index-time fields cannot be easily changed retroactively.

NEW QUESTION # 19
Buttercup games has implemented over 100 detections in their SOC. These detections consist mostly of vendor provided signatures and field matching that have been tuned, with a few that have been custom built. What more advanced detection methods should they deploy?

A. Enrich with asset and identity information
B. Use an outlier based algorithm
C. Use automation to pull additional data
D. Define breaches of static thresholds

Answer: B

Explanation:
An outlier-based algorithm is a more advanced detection method because it uses behavioral or statistical analysis to identify activity that deviates from expected patterns. This moves beyond tuned signatures and field matching into anomaly-based detection, which can help uncover unknown or subtle threats.

NEW QUESTION # 20
Which of the following best describes "detection as code" as a practice relevant to a Cybersecurity Defense Architect?

A. Manually recreating detections after every Splunk upgrade
B. Managing correlation searches and detection logic under version control with testing and CI/CD pipelines
C. Writing detections exclusively in Python outside of Splunk
D. Avoiding documentation of detection logic

Answer: B

Explanation:
Detection as code refers to treating detection content (correlation searches, lookups, playbooks) as version-controlled, testable, and deployable artifacts, improving consistency, auditability, and change management.

NEW QUESTION # 21
Which of the following are valid use cases for the MLTK (Machine Learning Toolkit) in a security context? (Choose all that apply.)

A. Anomaly detection on network traffic volume
B. Predicting future login failure trends
C. Clustering similar security events for triage
D. Automatically writing SPL search queries

Answer: A,B,C

Explanation:
MLTK supports anomaly detection, predictive analytics (e.g., forecasting), and clustering algorithms applicable to security data; it does not autonomously write SPL queries, which remains a manual/analyst task.

NEW QUESTION # 22
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