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Splunk SPLK-5002 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Engineering: This section of the exam measures the skills of Security Analysts and Cybersecurity Engineers and covers foundational data management tasks. It includes performing data review and analysis, creating and maintaining efficient data indexing, and applying Splunk methods for data normalization to ensure structured and usable datasets for security operations.
Topic 2	Auditing and Reporting on Security Programs: This section tests Auditors and Security Architects on validating and communicating program effectiveness. It includes designing security metrics, generating compliance reports, and building dashboards to visualize program performance and vulnerabilities for stakeholders.
Topic 3	Building Effective Security Processes and Programs: This section targets Security Program Managers and Compliance Officers, focusing on operationalizing security workflows. It involves researching and integrating threat intelligence, applying risk and detection prioritization methodologies, and developing documentation or standard operating procedures (SOPs) to maintain robust security practices.
Topic 4	Detection Engineering: This section evaluates the expertise of Threat Hunters and SOC Engineers in developing and refining security detections. Topics include creating and tuning correlation searches, integrating contextual data into detections, applying risk-based modifiers, generating actionable Notable Events, and managing the lifecycle of detection rules to adapt to evolving threats.
Topic 5	Automation and Efficiency: This section assesses Automation Engineers and SOAR Specialists in streamlining security operations. It covers developing automation for SOPs, optimizing case management workflows, utilizing REST APIs, designing SOAR playbooks for response automation, and evaluating integrations between Splunk Enterprise Security and SOAR tools.

Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q60-Q65):

NEW QUESTION # 60
What elements are critical for developing meaningful security metrics? (Choose three)

A. Relevance to business objectives
B. Avoiding integration with third-party tools
C. Consistent definitions for key terms
D. Visual representation through dashboards
E. Regular data validation

Answer: A,C,E

Explanation:
Key Elements of Meaningful Security Metrics
Security metrics shouldalign with business goals, be validated regularly, and have standardized definitionsto ensure reliability.
#1. Relevance to Business Objectives (A)
Security metrics should tie directly tobusiness risks and priorities.
Example:
A financial institution might trackfraud detection ratesinstead of genericmalware alerts.
#2. Regular Data Validation (B)
Ensures data accuracy byremoving false positives, duplicates, and errors.
Example:
Validatingphishing alert effectivenessby cross-checking withuser-reported emails.
#3. Consistent Definitions for Key Terms (E)
Standardized definitions preventmisinterpretation of security metrics.
Example:
Clearly definingMTTD (Mean Time to Detect) vs. MTTR (Mean Time to Respond).
#Incorrect Answers:
C: Visual representation through dashboards# Dashboards help, butdata quality matters more.
D: Avoiding integration with third-party tools# Integrations withSIEM, SOAR, EDR, and firewallsarecrucial for effective metrics.
#Additional Resources:
NIST Security Metrics Framework
Splunk

NEW QUESTION # 61
A company wants to create a dashboard that displays normalized event data from various sources.
Whatapproach should they use?

A. Configure a summary index.
B. Implement a data model using CIM.
C. Apply search-time field extractions.
D. Use SPL queries to manually extract fields.

Answer: B

Explanation:
When organizations need to normalize event data from various sources, using Common Information Model (CIM) in Splunk is the best approach.
Why Use CIM for Normalized Event Data?
Standardizes Data Across Different Log Sources
CIM ensures consistent field names and formats across varied log types.
Makes searches, reports, and dashboards easier to manage.
Enables Faster and More Efficient Searches
Uses Data Models to accelerate search queries.
Reduces the need for custom field extractions.

NEW QUESTION # 62
A security engineer is tasked with improving threat intelligence sharing within the company.
Whatis the most effective first step?

A. Restrict access to external threat intelligence sources.
B. Share raw threat data with all employees.
C. Implement a real-time threat feed integration.
D. Use threat intelligence only for executive reporting.

Answer: C

Explanation:
Improving Threat Intelligence Sharing in an Organization
Threat intelligence enhances cybersecurity by providing real-time insights into emerging threats.
#1. Implement a Real-Time Threat Feed Integration (A)
Enables real-time ingestion of threat indicators (IOCs, IPs, hashes, domains).
Helps automate threat detection and blocking.
Example:
Integrating STIX/TAXII, Splunk Threat Intelligence Framework, or a SOAR platform for live threat updates.
#Incorrect Answers:
B: Restrict access to external threat intelligence sources # Sharing intelligence enhances security, not restricting it.
C: Share raw threat data with all employees # Raw intelligence needs analysis and context before distribution.
D: Use threat intelligence only for executive reporting # SOC analysts, incident responders, and IT teams need actionable intelligence.
#Additional Resources:
Splunk Threat Intelligence Framework
How to Integrate STIX/TAXII in Splunk

NEW QUESTION # 63
Which practices strengthen the development of Standard Operating Procedures (SOPs)?(Choosethree)

A. Excluding historical incident data
B. Focusing solely on high-risk scenarios
C. Collaborating with cross-functional teams
D. Regular updates based on feedback
E. Including detailed step-by-step instructions

Answer: C,D,E

Explanation:
Why Are These Practices Essential for SOP Development?
Standard Operating Procedures (SOPs)are crucial for ensuring consistent, repeatable, and effective security operations in aSecurity Operations Center (SOC). Strengthening SOP development ensuresefficiency, clarity, and adaptabilityin responding to incidents.
1##Regular Updates Based on Feedback (Answer A)
Security threats evolve, andSOPs must be updatedbased onreal-world incidents, analyst feedback, and lessons learned.
Example: Anew ransomware variantis detected; theSOP is updatedto include aspecific containment playbookin Splunk SOAR.
2##Collaborating with Cross-Functional Teams (Answer C)
Effective SOPs requireinput from SOC analysts, threat hunters, IT, compliance teams, and DevSecOps.
Ensures thatall relevant security and business perspectivesare covered.
Example: ASOC team collaborates with DevOpsto ensure that acloud security response SOPaligns with AWS security controls.
3##Including Detailed Step-by-Step Instructions (Answer D)
SOPs should provideclear, actionable, and standardizedsteps for security analysts.
Example: ASplunk ES incident response SOPshould include:
How to investigate a security alertusing correlation searches.
How to escalate incidentsbased on risk levels.
How to trigger a Splunk SOAR playbookfor automated remediation.
Why Not the Other Options?
#B. Focusing solely on high-risk scenarios-All security events matter, not just high-risk ones.Low-level alertscan be early indicators of larger threats.#E. Excluding historical incident data- Past incidents providevaluable lessonsto improveSOPs and incident response workflows.
References & Learning Resources
#Best Practices for SOPs in Cybersecurity:https://www.nist.gov/cybersecurity-framework#Splunk SOAR Playbook SOP Development: https://docs.splunk.com/Documentation/SOAR#Incident Response SOPs with Splunk: https://splunkbase.splunk.com

NEW QUESTION # 64
What is the primary purpose of data indexing in Splunk?

A. To secure data from unauthorized access
B. To visualize data using dashboards
C. To store raw data and enable fast search capabilities
D. To ensure data normalization

Answer: C

Explanation:
Understanding Data Indexing in Splunk
In Splunk Enterprise Security (ES) and Splunk SOAR, data indexing is a fundamental process that enables efficient storage, retrieval, and searching of data.
#Why is Data Indexing Important?
Stores raw machine data (logs, events, metrics) in a structured manner.
Enables fast searching through optimized data storage techniques.
Uses an indexer to process, compress, and store data efficiently.
Why the Correct Answer is B?
Splunk indexes data to store it efficiently while ensuring fast retrieval for searches, correlation searches, and analytics.
It assigns metadata to indexed events, allowing SOC analysts to quickly filter and search logs.
#Incorrect Answers & Explanations
A: To ensure data normalization # Splunk normalizes data using Common Information Model (CIM), not indexing.
C: To secure data from unauthorized access # Splunk uses RBAC (Role-Based Access Control) and encryption for security, not indexing.
D: To visualize data using dashboards # Dashboards use indexed data for visualization, but indexing itself is focused on data storage and retrieval.
#Additional Resources:
Splunk Data Indexing Documentation
Splunk Architecture & Indexing Guide

NEW QUESTION # 65
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SPLK-5002 CERT GUIDE | EXAM TOPICS SPLK-5002 PDF

SPLK-5002 Cert Guide | Exam Topics SPLK-5002 Pdf