SPLK-5002 Exam Learning, Reliable SPLK-5002 Test Bootcamp
SPLK-5002 Exam Learning, Reliable SPLK-5002 Test Bootcamp
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Tags: SPLK-5002 Exam Learning, Reliable SPLK-5002 Test Bootcamp, SPLK-5002 Real Exam, SPLK-5002 Prep Guide, SPLK-5002 Pdf Exam Dump
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Splunk SPLK-5002 Exam Syllabus Topics:
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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q25-Q30):
NEW QUESTION # 25
What is the purpose of leveraging REST APIs in a Splunk automation workflow?
- A. To configure storage retention policies
- B. To compress data before indexing
- C. To integrate Splunk with external applications and automate interactions
- D. To generate predefined reports
Answer: C
Explanation:
Splunk's REST API allows external applications and security tools to automate workflows, integrate with Splunk, and retrieve/search data programmatically.
#Why Use REST APIs in Splunk Automation?
Automates interactions between Splunk and other security tools.
Enables real-time data ingestion, enrichment, and response actions.
Used in Splunk SOAR playbooks for automated threat response.
Example:
A security event detected in Splunk ES triggers a Splunk SOAR playbook via REST API to:
Retrieve threat intelligence from VirusTotal.
Block the malicious IP in Palo Alto firewall.
Create an incident ticket in ServiceNow.
#Incorrect Answers:
A: To configure storage retention policies # Storage is managed via Splunk indexing, not REST APIs.
C: To compress data before indexing # Splunk does not use REST APIs for data compression.
D: To generate predefined reports # Reports are generated using Splunk's search and reporting functionality, not APIs.
#Additional Resources:
Splunk REST API Documentation
Automating Workflows with Splunk API
NEW QUESTION # 26
What is the role of aggregation policies in correlation searches?
- A. To automate responses to critical events
- B. To group related notable events for analysis
- C. To normalize event fields for dashboards
- D. To index events from multiple sources
Answer: B
Explanation:
Aggregation policies in Splunk Enterprise Security (ES) are used to group related notable events, reducing alert fatigue and improving incident analysis.
Role of Aggregation Policies in Correlation Searches:
Group Related Notable Events (A)
Helps SOC analysts see a single consolidated event instead of multiple isolated alerts.
Uses common attributes like user, asset, or attack type to aggregate events.
Improves Incident Response Efficiency
Reduces the number of duplicate alerts, helping analysts focus on high-priority threats.
NEW QUESTION # 27
What are the benefits of incorporating asset and identity information into correlation searches?(Choosetwo)
- A. Reducing the volume of raw data indexed
- B. Enhancing the context of detections
- C. Prioritizing incidents based on asset value
- D. Accelerating data ingestion rates
Answer: B,C
Explanation:
Why is Asset and Identity Information Important in Correlation Searches?
Correlation searches in Splunk Enterprise Security (ES) analyze security events to detect anomalies, threats, and suspicious behaviors. Adding asset and identity information significantly improves security detection and response by:
1##Enhancing the Context of Detections - (Answer A)
Helps analysts understand the impact of an event by associating security alerts with specific assets and users.
Example: If a failed login attempt happens on a critical server, it's more serious than one on a guest user account.
2##Prioritizing Incidents Based on Asset Value - (Answer C)
High-value assets (CEO's laptop, production databases) need higher priority investigations.
Example: If malware is detected on a critical finance server, the SOC team prioritizes it over a low-impact system.
Why Not the Other Options?
#B. Reducing the volume of raw data indexed - Asset and identity enrichment adds more metadata;it doesn't reduce indexed data.#D. Accelerating data ingestion rates - Adding asset identity doesn't speed up ingestion; it actually introduces more processing.
References & Learning Resources
#Splunk ES Asset & Identity Framework: https://docs.splunk.com/Documentation/ES/latest/Admin
/Assetsandidentitymanagement#Correlation Searches in Splunk ES: https://docs.splunk.com/Documentation
/ES/latest/Admin/Correlationsearches
NEW QUESTION # 28
What is the primary purpose of correlation searches in Splunk?
- A. To extract and index raw data
- B. To identify patterns and relationships between multiple data sources
- C. To store pre-aggregated search results
- D. To create dashboards for real-time monitoring
Answer: B
Explanation:
Correlation searches in Splunk Enterprise Security (ES) are a critical component of Security Operations Center (SOC) workflows, designed to detect threats by analyzing security data from multiple sources.
Primary Purpose of Correlation Searches:
Identify threats and anomalies: They detect patterns and suspicious activity by correlating logs, alerts, and events from different sources.
Automate security monitoring: By continuously running searches on ingested data, correlationsearches help reduce manual efforts for SOC analysts.
Generate notable events: When a correlation search identifies a security risk, it creates a notable event in Splunk ES for investigation.
Trigger security automation: In combination with Splunk SOAR, correlation searches can initiate automated response actions, such as isolating endpoints or blocking malicious IPs.
Since correlation searches analyze relationships and patterns across multiple data sources to detect security threats, the correct answer is B. To identify patterns and relationships between multiple data sources.
References:
Splunk ES Correlation Searches Overview
Best Practices for Correlation Searches
Splunk ES Use Cases and Notable Events
NEW QUESTION # 29
Which configurations are required for data normalization in Splunk?(Choosetwo)
- A. savedsearches.conf
- B. props.conf
- C. authorize.conf
- D. transforms.conf
- E. eventtypes.conf
Answer: B,D
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 # 30
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