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Splunk SPLK-5003 Exam Syllabus Topics:

Section	Weight	Objectives
Measuring and Improving Security Program Effectiveness	15%	- Security metrics and performance 1. Program maturity assessment 2. Risk measurement 3. Continuous improvement processes
Advanced Automation and Orchestration	10%	- SOAR architecture 1. Workflow automation 2. Playbook design 3. Security orchestration
Advanced Threat Intelligence and Analysis	5%	- Threat intelligence architecture 1. Threat intelligence integration 2. Advanced threat analysis 3. Threat-informed defense
Advanced Incident Response and Management	10%	- Incident response architecture 1. Incident management optimization 2. Response workflows 3. Investigation processes
Security Data Management	20%	- Data architecture design 1. Data quality and governance 2. Security data onboarding and normalization 3. Data lifecycle management
Governance, Risk and Compliance	10%	- Security governance 1. Compliance requirements 2. Policy alignment 3. Risk management frameworks
Scaling Cybersecurity Defenses and DevSecOps	15%	- Security architecture at scale 1. Enterprise security operations design 2. DevSecOps integration 3. Scalable defense strategies
Security Capability Selection, Placement and Configuration	15%	- Security control architecture 1. Capability integration 2. Control placement strategies 3. Technology selection

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Splunk Certified Cybersecurity Defense Architect Sample Questions (Q116-Q121):

NEW QUESTION # 116
Which of the following tasks takes the largest portion of a data scientist's time?

A. Building ML infrastructure
B. Building AI agents
C. Data analysis and modeling
D. Data cleaning and preparation

Answer: D

Explanation:
Data cleaning and preparation typically take the largest portion of a data scientist's time because raw data must be collected, validated, normalized, enriched, and transformed before reliable analysis or modeling can occur.

NEW QUESTION # 117
Which of the following explains the benefits of modern cybersecurity defense data architectures using technologies such as data fabric, data lakes, message bus, and federated search?

A. They centralize all security data into a single repository to reduce complexity and improve access speed.
B. They protect and isolate security data ensuring safe data sharing.
C. They use local storage on each security appliance to reduce network traffic and eliminate the need for search capabilities.
D. They distribute data storage and processing, enabling different teams to manage and consume data as needed to meet their use cases.

Answer: D

Explanation:
Modern cybersecurity data architectures distribute storage, processing, routing, and access so different teams can use the right data in the right place for their specific detection, investigation, analytics, retention, and compliance needs. This avoids forcing all telemetry into one platform while still enabling broad visibility and flexible consumption.

NEW QUESTION # 118
Which approach most effectively minimizes the risk of secret exposure in CI/CD pipelines while also supporting automated deployments?

A. Using a dedicated secrets management service to provide secrets only to authorized jobs.
B. Hardcoding secrets in configuration files that are excluded from version control using .gitignore.
C. Encrypting secrets and storing them in the same source code repository, then decrypting them at runtime.
D. Saving secrets as environment variables in shared CI/CD runner configuration files.

Answer: A

Explanation:
A dedicated secrets management service minimizes exposure by storing secrets outside source code and CI/CD configuration files, enforcing access controls, audit logging, rotation, and short- lived retrieval by authorized pipeline jobs. This supports automated deployments while reducing the chance that credentials are leaked, reused, or exposed broadly.

NEW QUESTION # 119
Which of the following best describes how data science, machine learning, behavioral analysis, and AI improve threat detection compared to traditional detection approaches?

A. They rely on defined rules and signatures to identify threats.
B. They highlight anomalies, relationships, and unique patterns to identify threats.
C. They rapidly integrate with legacy SIEM infrastructure to identify threats.
D. They escalate anomalies based on static thresholds to identify threats.

Answer: B

Explanation:
Data science, machine learning, behavioral analysis, and AI improve detection by identifying anomalies, relationships, and patterns that may not match predefined signatures or static rules.
This helps uncover unusual behavior, emerging threats, and subtle attack activity across large or complex datasets.

NEW QUESTION # 120
As part of an incident response plan, the SOC team needs to ensure that compromised internal host IP addresses are automatically isolated from the network. How can the security architect achieve this using Splunk ES and network infrastructure?

A. Create an Adaptive Response Action in Splunk ES that triggers a script or SOAR playbook to update the firewall or NAC appliance to quarantine the IP.
B. Write a complex SPL query that deletes the malicious traffic logs from the indexer, thereby stopping the attack.
C. Configure the splunkd service to act as a proxy and block the traffic directly at the Search Head.
D. Use the Splunk Universal Forwarder installed on the firewall to change the firewall's routing table.

Answer: A

Explanation:
Splunk ES uses Adaptive Response Actions to execute tasks in response to notable events or correlation search triggers. Triggering a SOAR playbook or an integrated script to interact with network infrastructure (such as a firewall or Network Access Control system) is the standard architectural method for automating host isolation.

NEW QUESTION # 121
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