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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q55-Q60):

NEW QUESTION # 55
Which REST API method is used to retrieve data from a Splunk index?

  • A. GET
  • B. DELETE
  • C. PUT
  • D. POST

Answer: A

Explanation:
The GET method in the Splunk REST API is used to retrieve data from a Splunk index. It allows users and automated scripts to fetch logs, alerts, or query results programmatically.
Key Points About GET in Splunk API:
Used for searching and retrieving logs from indexes.
Can be used to get search results, job status, and Splunk configuration details.
Common API endpoints include:
/services/search/jobs/{search_id}/results- Retrieves results of a completed search.
/services/search/jobs/export- Exports search results in real-time.


NEW QUESTION # 56
What is the primary function of summary indexing in Splunk reporting?

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

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 # 57
A Splunk administrator needs to integrate a third-party vulnerability management tool to automate remediation workflows.
Whatis the most efficient first step?

  • A. Use REST APIs to integrate the third-party tool with Splunk SOAR
  • B. Write a correlation search for each vulnerability type
  • C. Configure custom dashboards to monitor vulnerabilities
  • D. Set up a manual alerting system for vulnerabilities

Answer: A

Explanation:
Why Use REST APIs for Integration?
When integrating a third-party vulnerability management tool (e.g., Tenable, Qualys, Rapid7) with Splunk SOAR, using REST APIs is the most efficient and scalable approach.
#Why REST APIs?
APIs enable direct communication between Splunk SOAR and the third-party tool.
Allows automated ingestion of vulnerability data into Splunk.
Supports automated remediation workflows (e.g., patch deployment, firewall rule updates).
Reduces manual work by allowing Splunk SOAR to pull real-time data from the vulnerability tool.
Steps to Integrate a Third-Party Vulnerability Tool with Splunk SOAR Using REST API:
1##Obtain API Credentials - Get API keys or authentication tokens from the vulnerability management tool.
2##Configure REST API Integration - Use Splunk SOAR's built-in API connectors or create a custom REST API call.3##Ingest Vulnerability Data into Splunk - Map API responses to Splunk ES correlation searches.
4##Automate Remediation Playbooks - Build Splunk SOAR playbooks to:
Automatically open tickets for critical vulnerabilities.
Trigger patches or firewall rules for high-risk vulnerabilities.
Notify SOC analysts when a high-risk vulnerability is detected on a critical asset.
Example Use Case in Splunk SOAR:
#Scenario: The company uses Tenable.io for vulnerability management.#Splunk SOAR connects to Tenable's API and pulls vulnerability scan results.#If a critical vulnerability is found on a production server, Splunk SOAR:
Automatically creates a ServiceNow ticket for remediation.
Triggers a patching script to fix the vulnerability.
Updates Splunk ES dashboards for tracking.
Why Not the Other Options?
#A. Set up a manual alerting system for vulnerabilities - Manual alerting is inefficient and doesn't scale well.
#C. Write a correlation search for each vulnerability type - This would create too many rules; API integration allows real-time updates from the vulnerability tool.#D. Configure custom dashboards to monitor vulnerabilities - Dashboards provide visibility but don't automate remediation.
References & Learning Resources
#Splunk SOAR API Integration Guide: https://docs.splunk.com/Documentation/SOAR#Integrating Tenable, Qualys, Rapid7 with Splunk: https://splunkbase.splunk.com#REST API Automation in Splunk SOAR:
https://www.splunk.com/en_us/products/soar.html


NEW QUESTION # 58
Which configurations are required for data normalization in Splunk?(Choosetwo)

  • A. transforms.conf
  • B. savedsearches.conf
  • C. props.conf
  • D. authorize.conf
  • E. eventtypes.conf

Answer: A,C

Explanation:
Configurations Required for Data Normalization in Splunk
Data normalization ensures consistent field naming and event structuring, especially for Splunk Common Information Model (CIM) compliance.
#1. props.conf (A)
Defines how data is parsed and indexed.
Controls field extractions, event breaking, and timestamp recognition.
Example:
Assigns custom sourcetypes and defines regex-based field extraction.
#2. transforms.conf (B)
Used for data transformation, lookup table mapping, and field aliasing.
Example:
Normalizes firewall logs by renaming src_ip # src to align with CIM.
#Incorrect Answers:
C: savedsearches.conf # Defines scheduled searches, not data normalization.
D: authorize.conf # Manages user permissions, not data normalization.
E: eventtypes.conf # Groups events into categories but doesn't modify data structure.
#Additional Resources:
Splunk Data Normalization Guide
Understanding props.conf and transforms.conf


NEW QUESTION # 59
What feature allows you to extract additional fields from events at search time?

  • A. Data modeling
  • B. Event parsing
  • C. Search-time field extraction
  • D. Index-time field extraction

Answer: C

Explanation:
Splunk allows dynamic field extraction to enhance data analysis without modifying raw indexed data.
Search-Time Field Extraction:
Extracts fields on-demand when running searches.
Uses Splunk's Field Extraction Engine (rex,spath, or automatic field discovery).
Minimizes indexing overhead by keeping the raw data unchanged.


NEW QUESTION # 60
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