SPLK-5003 Exam Dumps | Latest Valid Braindumps SPLK-5003 Questions: Splunk Certified Cybersecurity Defense Architect

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Splunk SPLK-5003 Exam Syllabus Topics:

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

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Splunk Certified Cybersecurity Defense Architect Sample Questions (Q29-Q34):

NEW QUESTION # 29
An architect needs to design detections that leverage user behavior baselines to flag anomalies such as impossible travel. Which Splunk technology is best suited?

A. KV Store lookups
B. Data model acceleration
C. UEBA (User and Entity Behavior Analytics)
D. Metrics indexes

Answer: C

Explanation:
Splunk UEBA is purpose-built for behavioral baselining and anomaly detection across users and entities, including detecting anomalies like impossible travel based on statistical and machine learning models.

NEW QUESTION # 30
A threat hunter is looking for suspicious login activity across multiple different authentication systems and cloud providers. Today, the threat hunter has to query multiple different data sources with unique logic to gather basic information about authentication events. What method provides a simple way to standardize data formats, and look for common activity across different sources?

A. Data normalization
B. Calculated fields
C. Adaptive Response Actions
D. Risk-based alerting

Answer: A

Explanation:
Data normalization standardizes fields and event structures across different authentication systems and cloud providers. This allows threat hunters to search for common login activity using consistent field names and logic instead of writing separate queries for each unique data source.

NEW QUESTION # 31
Which of the following are valid considerations when prioritizing data source onboarding for a SIEM? (Choose all that apply.)

A. Existing detection coverage gaps
B. Alignment with the organization's top threat scenarios
C. Vendor marketing popularity
D. Data source licensing cost

Answer: A,B,D

Explanation:
Data source onboarding should be prioritized based on relevance to threat scenarios, licensing/ingestion cost impact, and closing detection coverage gaps -- not on vendor popularity, which is not a security-relevant criterion.

NEW QUESTION # 32
A security architect is tasked with implementing a Zero Trust architecture monitoring strategy. Which data sources are MOST critical to ingest into Splunk to monitor the continuous verification of identities and devices?

A. External DNS query logs and generic network flow data
B. Identity and Access Management (IAM) logs, Multi-Factor Authentication (MFA) logs, and Endpoint Detection and Response (EDR) telemetry
C. Web server access logs and database query execution times
D. Physical badge reader logs and HVAC telemetry

Answer: B

Explanation:
Zero Trust security models are built on the principle of continuous verification of user identities, device health, and access context before granting access. Therefore, IAM logs, MFA logs (identity verification), and EDR telemetry (device posture/health) are the most critical data sources to monitor the core pillars of a Zero Trust architecture.

NEW QUESTION # 33
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 distribute data storage and processing, enabling different teams to manage and consume data as needed to meet their use cases.
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 centralize all security data into a single repository to reduce complexity and improve access speed.

Answer: A

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 # 34
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