Guaranteed Success with Splunk SPLK-5002 Dumps
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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q19-Q24):
NEW QUESTION # 19
What is the primary purpose of developing security metrics in a Splunk environment?
- A. To automate case management workflows
- B. To measure and evaluate the effectiveness of security programs
- C. To enhance data retention policies
- D. To identify low-priority alerts for suppression
Answer: B
Explanation:
Security metrics help organizations assess their security posture and make data-driven decisions.
Primary Purpose of Security Metrics in Splunk:
Measure Security Effectiveness (B)
Tracks incident response times, threat detection rates, and alert accuracy.
Helps SOC teams and leadership evaluate security program performance.
Improve Threat Detection & Incident Response
Identifies gaps in detection logic and false positives.
Helps fine-tune correlation searches and notable events.
NEW QUESTION # 20
Which Splunk Enterprise Security add-on facilitates the ingestion of Threat Intelligence data?
- A. ESS-Intel
- B. SA-ThreatIntelligence
- C. TA-ThreatIntel
- D. SA-ESSIntel
Answer: B
Explanation:
The SA-ThreatIntelligence add-on in Splunk Enterprise Security is responsible for ingesting and normalizing threat intelligence data. It manages threat feeds and ensures they are available for correlation searches and risk analysis within ES.
NEW QUESTION # 21
When creating detections, which of the following sequences would result in the most performant SPL query?
- A. Define base query, minimize data, combine/summarize data, execute calculations, format the data
- B. Define base query, minimize data, combine/summarize data, format the data, execute calculations
- C. Define base query, combine/summarize data, minimize data, execute calculations, format the data
- D. Define base query, minimize data, format the data, combine/summarize data, execute calculations
Answer: A
Explanation:
The most performant SPL query sequence is:
Define base query → Minimize data → Combine/Summarize data → Execute calculations → Format the data.
Minimizing the data early (using filters, time constraints, and field limitations) reduces the dataset before expensive operations like summarization or calculations, resulting in optimal performance.
NEW QUESTION # 22
Which actions enhance the accuracy of Splunk dashboards?(Choosetwo)
- A. Using accelerated data models
- B. Disabling drill-down features
- C. Avoiding token-based filters
- D. Performing regular data validation
Answer: A,D
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 # 23
The threat-hunting team has identified suspicious activity. An analyst manually creates a notable event using an event action to track the activity. How should a detection engineer ensure this activity automatically produces findings in the future?
- A. Create a correlation search to produce notable events for the activity.
- B. Create a risk modifier for events matching the activity.
- C. Create a SOAR playbook to assign risk modifiers for events matching the activity.
- D. Create a SOAR playbook to identify events matching the activity and assign an urgency.
Answer: A
Explanation:
To ensure that suspicious activity consistently generates findings in the future, the detection engineer should create a correlation search for the identified activity. This automates detection by continuously monitoring for the same pattern and producing notable events when it occurs again.
NEW QUESTION # 24
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