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SPLK-5002 Test Questions & Latest SPLK-5002 Mock Test

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Latest Splunk SPLK-5002 Mock Test, SPLK-5002 Latest Study Notes

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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

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 3

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 4

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 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 (Q73-Q78):

NEW QUESTION # 73
A security analyst wants to validate whether a newly deployed SOAR playbook is performing as expected.
Whatsteps should they take?

A. Monitor the playbook's actions in real-time environments
B. Automate all tasks within the playbook immediately
C. Compare the playbook to existing incident response workflows
D. Test the playbook using simulated incidents

Answer: D

Explanation:
A SOAR (Security Orchestration, Automation, and Response) playbook is a set of automated actions designed to respond to security incidents. Before deploying it in a live environment, a security analyst must ensure that it operates correctly, minimizes false positives, and doesn't disrupt business operations.
#Key Reasons for Using Simulated Incidents:
Ensures that the playbook executes correctly and follows the expected workflow.
Identifies false positives or incorrect actions before deployment.
Tests integrations with other security tools (SIEM, firewalls, endpoint security).
Provides a controlled testing environment without affecting production.
How to Test a Playbook in Splunk SOAR?
1##Use the "Test Connectivity" Feature - Ensures that APIs and integrations work.2##Simulate an Incident - Manually trigger an alert similar to a real attack (e.g., phishing email or failed admin login).3##Review the Execution Path - Check each step in the playbook debugger to verify correct actions.4##Analyze Logs & Alerts - Validate that Splunk ES logs, security alerts, and remediation steps are correct.5##Fine-tune Based on Results - Modify the playbook logic to reduce unnecessary alerts or excessive automation.
Why Not the Other Options?
#B. Monitor the playbook's actions in real-time environments - Risky without prior validation. Itcan cause disruptions if the playbook misfires.#C. Automate all tasks immediately - Not best practice. Gradual deployment ensures better security control and monitoring.#D. Compare with existing workflows - Good practice, but it does not validate the playbook's real execution.
References & Learning Resources
#Splunk SOAR Documentation: https://docs.splunk.com/Documentation/SOAR#Testing Playbooks in Splunk SOAR: https://www.splunk.com/en_us/products/soar.html#SOAR Playbook Debugging Best Practices:
https://splunkbase.splunk.com

NEW QUESTION # 74
What are the essential components of risk-based detections in Splunk?

A. Summary indexing, tags, and event types
B. Risk modifiers, risk objects, and risk scores
C. Source types, correlation searches, and asset groups
D. Alerts, notifications, and priority levels

Answer: B

Explanation:
What Are Risk-Based Detections in Splunk?
Risk-based detections in Splunk Enterprise Security (ES) assign risk scores to security events based on threat severity and asset criticality.
#Key Components of Risk-Based Detections:1##Risk Modifiers - Adjusts risk scores based on event type (e.
g., failed logins, malware detections).2##Risk Objects - Entities associated with security events (e.g., users, IPs, devices).3##Risk Scores - Numerical values indicating the severity of a risk.
#Example in Splunk Enterprise Security:#Scenario: A high-privilege account (Admin) fails multiple logins from an unusual location.#Splunk ES applies risk-based detection:
Failed logins add +10 risk points
Login from a suspicious country adds +15 points
Total risk score exceeds 25 # Triggers an alert
Why Not the Other Options?
#B. Summary indexing, tags, and event types - Summary indexing stores precomputed data, but doesn't drive risk-based detection.#C. Alerts, notifications, and priority levels - Important, but risk-based detection is based on scoring, not just alerts.#D. Source types, correlation searches, and asset groups - Helps in data organization, but not specific to risk-based detections.
References & Learning Resources
#Splunk ES Risk-Based Alerting Guide: https://docs.splunk.com/Documentation/ES#Risk-Based Detections
& Scoring in Splunk: https://www.splunk.com/en_us/blog/security/risk-based-alerting.html#Best Practices for Risk Scoring in SOC Operations: https://splunkbase.splunk.com

NEW QUESTION # 75
A Splunk administrator is tasked with creating a weekly security report for executives.
Whatelements should they focus on?

A. Detailed logs of every notable event
B. Excluding compliance metrics to simplify reports
C. High-level summaries and actionable insights
D. Avoiding visuals to focus on raw data

Answer: C

Explanation:
Why Focus on High-Level Summaries & Actionable Insights?
Executive security reports should provideconcise, strategic insightsthat help leadership teams makeinformed decisions.
#Key Elements for an Executive-Level Report:#Summarized Security Incidents- Focus onmajor threats and trends.#Actionable Recommendations- Includemitigation stepsfor ongoing risks.#Visual Dashboards- Use charts and graphs foreasy interpretation.#Compliance & Risk Metrics- Highlightcompliance status(e.g., PCI- DSS, NIST).
#Example in Splunk:#Scenario:A CISO requests aweekly security report.#Best Report Format:
Threat Summary:"Detected 15 phishing attacks this week."
Key Risks:"Increase in brute-force login attempts."
Recommended Actions:"Enhance MFA enforcement & user awareness training." Why Not the Other Options?
#B. Detailed logs of every notable event- Too technical; executives needsummaries, not raw logs.#C.
Excluding compliance metrics to simplify reports- Compliance is critical forrisk assessment.#D. Avoiding visuals to focus on raw data-Visuals improve clarity; raw data is too complex for executives.
References & Learning Resources
#Splunk Security Reporting Best Practices: https://www.splunk.com/en_us/blog/security#Creating Effective Executive Dashboards in Splunk: https://splunkbase.splunk.com#Cybersecurity Metrics & Reporting for Leadership Teams:https://www.nist.gov/cyberframework

NEW QUESTION # 76
Which actions enhance the accuracy of Splunk dashboards?(Choosetwo)

A. Performing regular data validation
B. Avoiding token-based filters
C. Using accelerated data models
D. Disabling drill-down features

Answer: A,C

Explanation:
How to Improve Dashboard Accuracy in Splunk?
#1. Using Accelerated Data Models (Answer A)#Increases search speedand ensuresdashboards load faster.
#Provides pre-processed structured dataforreal-time analysis.#Example:ASOC dashboard tracking failed loginsuses an accelerated authentication data model forfaster rendering.
#2. Performing Regular Data Validation (Answer C)#Ensures that the indexed data is accurate and complete.
#Prevents misleading dashboardscaused by incomplete logs or incorrect field extractions.#Example:If afirewall log source stops sending data, regular validation detects missing logsbefore analysts rely on incorrect dashboards.
Why Not the Other Options?
#B. Avoiding token-based filters- Tokensimprovedashboard flexibility; avoiding themreduces usability.#D.
Disabling drill-down features- Drill-downsenhance insightsby allowing analysts to investigate details easily.
References & Learning Resources
#Splunk Dashboard Performance Optimization: https://docs.splunk.com/Documentation/Splunk/latest/Viz
/Dashboards#Using Data Models for Fast and Accurate Dashboards: https://splunkbase.splunk.com#Regular Data Validation for SOC Dashboards: https://www.splunk.com/en_us/blog/security

NEW QUESTION # 77
What is the primary function of summary indexing in Splunk reporting?

A. Creating pre-aggregated data for faster reporting
B. Storing unprocessed log data
C. Normalizing raw data for analysis
D. Enhancing the accuracy of alerts

Answer: A

Explanation:
Primary Function of Summary Indexing in Splunk Reporting
Summary indexing allows pre-aggregation of data to improve performance and speed up reports.
#Why Use Summary Indexing?
Reduces processing time by storing computed results instead of raw data.
Helps SOC teams generate reports faster and optimize search performance.
Example:
Instead of searching millions of firewall logs in real-time, a summary index stores daily aggregated counts of blocked IPs.
#Incorrect Answers:
A: Storing unprocessed log data # Raw logs are stored in primary indexes, not summary indexes.
C: Normalizing raw data for analysis # Normalization is handled by CIM and data models.
D: Enhancing the accuracy of alerts # Summary indexing improves reporting performance, not alert accuracy.
#Additional Resources:
Splunk Summary Indexing Guide
Optimizing SIEM Reports in Splunk

NEW QUESTION # 78
......

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