SPLK-5002 EXAM PATTERN & LATEST SPLK-5002 EXAM TEST

SPLK-5002 Exam Pattern & Latest SPLK-5002 Exam Test

SPLK-5002 Exam Pattern & Latest SPLK-5002 Exam Test

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Tags: SPLK-5002 Exam Pattern, Latest SPLK-5002 Exam Test, SPLK-5002 Test Dumps, Instant SPLK-5002 Download, Reliable SPLK-5002 Exam Materials

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The Exam4Free is a leading platform that has been assisting the Splunk SPLK-5002 exam candidates for many years. Over this long time period countless SPLK-5002 exam candidates have passed their Splunk SPLK-5002 Exam. They got success in Splunk Certified Cybersecurity Defense Engineer exam with flying colors and did a job in top world companies.

Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q15-Q20):

NEW QUESTION # 15
Which sourcetype configurations affect data ingestion?(Choosethree)

  • A. Event breaking rules
  • B. Data retention policies
  • C. Timestamp extraction
  • D. Line merging rules

Answer: A,C,D

Explanation:
The sourcetype in Splunk defines how incoming machine data is interpreted, structured, and stored. Proper sourcetype configurations ensure accurate event parsing, indexing, and searching.
#1. Event Breaking Rules (A)
Determines how Splunk splits raw logs into individual events.
If misconfigured, a single event may be broken into multiple fragments or multiple log lines may be combined incorrectly.
Controlled using LINE_BREAKER and BREAK_ONLY_BEFORE settings.
#2. Timestamp Extraction (B)
Extracts and assigns timestamps to events during ingestion.
Incorrect timestamp configuration leads to misplaced events in time-based searches.
Uses TIME_PREFIX, MAX_TIMESTAMP_LOOKAHEAD, and TIME_FORMAT settings.
#3. Line Merging Rules (D)
Controls whether multiline events should be combined into a single event.
Useful for logs like stack traces or multi-line syslog messages.
Uses SHOULD_LINEMERGE and LINE_BREAKER settings.
C: Data Retention Policies #
Affects storage and deletion, not data ingestion itself.
#Additional Resources:
Splunk Sourcetype Configuration Guide
Event Breaking and Line Merging


NEW QUESTION # 16
A security engineer is tasked with improving threat intelligence sharing within the company.
Whatis the most effective first step?

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

Answer: D

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 # 17
What methods enhance risk-based detection in Splunk?(Choosetwo)

  • A. Defining accurate risk modifiers
  • B. Enriching risk objects with contextual data
  • C. Limiting the number of correlation searches
  • D. Using summary indexing for raw events

Answer: A,B

Explanation:
Risk-based detection in Splunk prioritizes alerts based on behavior, threat intelligence, and business impact.
Enhancing risk scores and enriching contextual data ensures that SOC teams focus on the most critical threats.
Methods to Enhance Risk-Based Detection:
Defining Accurate Risk Modifiers (A)
Adjusts risk scores dynamically based on asset value, user behavior, and historical activity.
Ensures that low-priority noise doesn't overwhelm SOC analysts.
Enriching Risk Objects with Contextual Data (D)
Adds threat intelligence feeds, asset criticality, and user behavior data to alerts.
Improves incident triage and correlation of multiple low-level events into significant threats.


NEW QUESTION # 18
What are essential steps in developing threat intelligence for a security program?(Choosethree)

  • A. Conducting regular penetration tests
  • B. Creating dashboards for executives
  • C. Collecting data from trusted sources
  • D. Operationalizing intelligence through workflows
  • E. Analyzing and correlating threat data

Answer: C,D,E

Explanation:
Threat intelligence in Splunk Enterprise Security (ES) enhances SOC capabilities by identifying known attack patterns, suspicious activity, and malicious indicators.
Essential Steps in Developing Threat Intelligence:
Collecting Data from Trusted Sources (A)
Gather data from threat intelligence feeds (e.g., STIX, TAXII, OpenCTI, VirusTotal, AbuseIPDB).
Include internal logs, honeypots, and third-party security vendors.
Analyzing and Correlating Threat Data (C)
Use correlation searches to match known threat indicators against live data.
Identify patterns in network traffic, logs, and endpoint activity.
Operationalizing Intelligence Through Workflows (E)
Automate responses using Splunk SOAR (Security Orchestration, Automation, and Response).
Enhance alert prioritization by integrating intelligence into risk-based alerting (RBA).


NEW QUESTION # 19
What Splunk process ensures that duplicate data is not indexed?

  • A. Event parsing
  • B. Data deduplication
  • C. Indexer clustering
  • D. Metadata tagging

Answer: A

Explanation:
Splunk prevents duplicate data from being indexed through event parsing, which occurs during the data ingestion process.
How Event Parsing Prevents Duplicate Data:
Splunk's indexer parses incoming data and assigns unique timestamps, metadata, and event IDs to prevent reindexing duplicate logs.
CRC Checks (Cyclic Redundancy Checks) are applied to avoid duplicate event ingestion.
Index-time filtering and transformation rules help detect and drop repeated data before indexing.


NEW QUESTION # 20
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