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Splunk SPLK-5003 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Security Data Management20%- Data architecture design
  • 1. Security data onboarding and normalization
  • 2. Data quality and governance
  • 3. Data lifecycle management
Topic 2: Advanced Threat Intelligence and Analysis5%- Threat intelligence architecture
  • 1. Threat-informed defense
  • 2. Advanced threat analysis
  • 3. Threat intelligence integration
Topic 3: Security Capability Selection, Placement and Configuration15%- Security control architecture
  • 1. Technology selection
  • 2. Capability integration
  • 3. Control placement strategies
Topic 4: Advanced Automation and Orchestration10%- SOAR architecture
  • 1. Security orchestration
  • 2. Playbook design
  • 3. Workflow automation
Topic 5: Advanced Incident Response and Management10%- Incident response architecture
  • 1. Incident management optimization
  • 2. Investigation processes
  • 3. Response workflows
Topic 6: Scaling Cybersecurity Defenses and DevSecOps15%- Security architecture at scale
  • 1. DevSecOps integration
  • 2. Enterprise security operations design
  • 3. Scalable defense strategies
Topic 7: Governance, Risk and Compliance10%- Security governance
  • 1. Risk management frameworks
  • 2. Compliance requirements
  • 3. Policy alignment
Topic 8: Measuring and Improving Security Program Effectiveness15%- Security metrics and performance
  • 1. Risk measurement
  • 2. Program maturity assessment
  • 3. Continuous improvement processes

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Splunk Certified Cybersecurity Defense Architect Sample Questions (Q23-Q28):

NEW QUESTION # 23
At which stage of the DevOps CI/CD pipeline is it most effective to create an SBOM?

Answer: A

Explanation:
The build phase is generally the most appropriate stage for generating a Software Bill of Materials (SBOM) because it provides visibility into the software components and dependencies assembled into the resulting application artifact.
During a build, dependency managers, package-resolution processes, compilers, and build tools determine which components and versions are incorporated into the software.
Generating the SBOM at this stage enables the organization to associate component information with a particular build artifact.
The resulting inventory may include direct dependencies, transitive dependencies, library versions, package identifiers, and supplier information.
This improves vulnerability tracking, software supply-chain transparency, and incident-response readiness.
For example, when a vulnerability is disclosed in a third-party library, security engineers can compare the affected package against stored SBOMs to identify potentially vulnerable application builds.
CISA ' s guidance on SBOM document types recognizes that build-generated SBOMs can provide greater confidence in the correspondence between the component inventory and the resulting product artifact.
Generating an SBOM only during user acceptance testing or after production deployment may delay identification of vulnerable dependencies.
Requirements gathering occurs before the final dependency composition is established.
A mature implementation should regenerate the SBOM for each relevant build and associate it with the corresponding artifact version.
Official reference / study topic: CISA, Types of Software Bill of Materials Documents and Build-Generated SBOMs.


NEW QUESTION # 24
Which categories of SOAR playbooks are commonly used within a security operations center?
(Choose all that apply.)

Answer: B,C,D

Explanation:
Common SOC SOAR playbook categories include endpoint response, phishing investigation, and enrichment. These playbooks automate repeatable analyst tasks such as collecting endpoint context, analyzing reported phishing messages, detonating artifacts, enriching indicators, and gathering evidence to support triage and response.


NEW QUESTION # 25
Which of the following best describes how measuring the financial impact of a cybersecurity incident can help justify and obtain additional budget for the cybersecurity team?

Answer: C

Explanation:
Quantifying the financial consequences of cybersecurity incidents allows security leadership to connect technical investments with business risk reduction and measurable economic outcomes.
An incident ' s financial impact may include service disruption, lost revenue, incident-response expenses, forensic investigations, system restoration, legal costs, regulatory consequences, and reputational damage.
These costs can be incorporated into a risk-based financial analysis to evaluate the potential benefits of improved preventive, detective, and responsive controls.
For example, implementing improved endpoint detection and automated containment may reduce the expected duration and business impact of ransomware incidents.
Security architects can compare the estimated reduction in expected incident losses against implementation costs, operating expenditure, licensing, and personnel requirements.
This supports a defensible business case for additional funding.
The analysis should distinguish realized historical losses from modeled future risk. It should also account for uncertainty, control effectiveness, incident likelihood, and residual risk rather than assuming that every security investment produces guaranteed savings.
Options B, C, and D fail to establish a measurable relationship between security spending and organizational outcomes.
A strong cybersecurity budget proposal demonstrates how investment contributes to business continuity, operational resilience, and economically justified risk reduction.
Official reference / study topic: Splunk certification blueprint Objectives 6.4, 7.1-7.2, and 8.3: investment and risk justification.


NEW QUESTION # 26
Which MLTK command can be used with tstats in an ES detection to apply a machine learning model to the search results?

Answer: B

Explanation:
The Splunk Machine Learning Toolkit (MLTK) provides specialized Search Processing Language commands for applying statistical and machine-learning algorithms to security telemetry. Among the listed options, fit is the appropriate command because it trains a machine-learning model and applies that model to the current search results.
The tstats command efficiently retrieves aggregated information from indexed fields and accelerated data models. It can produce datasets containing activity frequencies, authentication counts, network connections, and other security measurements. These results can be passed into supported machine-learning algorithms for behavioral analysis and anomaly identification.
An example workflow is:
| tstats count where index=security by host
| fit DensityFunction count
The fit operation evaluates the resulting data and generates model-derived output for analysis.
However, an important distinction exists in Splunk ' s official documentation: `apply` is the dedicated command for applying a previously trained and saved model to new search results. That command is missing from the supplied choices. Therefore, B is the best available answer, but the question is technically imprecise if it specifically refers to an existing model.
summary describes a learned model, sample selects subsets of data, and cluster is not the MLTK operation being requested.
Official reference / study topic: Splunk Machine Learning Toolkit, Search Commands for Machine Learning: fit and apply; certification blueprint Objective 4.4.


NEW QUESTION # 27
Camille is building the high-level architecture and organizational requirements for a SOC modernization and automation initiative. The organization would like to use Splunk SOAR as the foundation of its new vision and strategy. What are some of the primary objectives this initiative should seek to achieve?

Answer: C

Explanation:
A SOC modernization and automation initiative using Splunk SOAR should aim to detect and respond faster, reduce repetitive manual work, and lower analyst fatigue. Automating enrichment, triage, containment, and case workflows helps reduce both detection and response times while improving analyst productivity.


NEW QUESTION # 28
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