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Splunk SPLK-5002 Prüfungs-Guide - SPLK-5002 Prüfungsfragen

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Splunk SPLK-5002 Prüfungsplan:

Thema
Einzelheiten

Thema 1

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.

Thema 2

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.

Thema 3

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.

Thema 4

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.

Thema 5

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.

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Splunk SPLK-5002 Prüfungsfragen, SPLK-5002 Echte Fragen

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Splunk Certified Cybersecurity Defense Engineer SPLK-5002 Prüfungsfragen mit Lösungen (Q74-Q79):

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

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

Antwort: D

Begründung:
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

75. Frage
What are the key components of Splunk's indexing process?(Choosethree)

A. Indexing
B. Parsing
C. Alerting
D. Searching
E. Input phase

Antwort: A,B,E

Begründung:
Key Components of Splunk's Indexing Process
Splunk's indexing process consists of multiple stages that ingest, process, and store data efficiently for search and analysis.
#1. Input Phase (E)
Collects data from sources (e.g., syslogs, cloud services, network devices).
Defines where the data comes from and applies pre-processing rules.
Example:
A firewall log is ingested from a syslog server into Splunk.
#2. Parsing (A)
Breaks raw data into individual events.
Applies rules for timestamp extraction, line breaking, and event formatting.
Example:
A multiline log file is parsed so that each log entry is a separate event.
#3. Indexing (C)
Stores parsed data in indexes to enable fast searching.
Assigns metadata like host, source, and sourcetype.
Example:
An index=firewall_logs contains all firewall-related events.
#Incorrect Answers:
B: Searching # Searching happens after indexing, not during the indexing process.
D: Alerting # Alerting is part of SIEM and detection, not indexing.
#Additional Resources:
Splunk Indexing Process Documentation
Splunk Data Processing Pipeline

76. Frage
What does Splunk's term "bucket" refer to in data indexing?

A. A collection of events with a specific retention policy
B. A directory containing indexed data
C. A storage unit for archived data
D. A database table for search results

Antwort: B

77. Frage
What methods improve the efficiency of Splunk's automation capabilities? (Choose three)

A. Employing prebuilt SOAR playbooks
B. Implementing low-latency indexing
C. Leveraging saved search acceleration
D. Using modular inputs
E. Optimizing correlation search queries

Antwort: A,D,E

Begründung:
How to Improve Splunk's Automation Efficiency?
Splunk's automation capabilities rely on efficient data ingestion, optimized searches, and automated response workflows. The following methods help improve Splunk's automation:
#1. Using Modular Inputs (Answer A)
Modular inputs allow Splunk to ingest third-party data efficiently (e.g., APIs, cloud services, or security tools).
Benefit: Improves automation by enabling real-time data collection for security workflows.
Example: Using a modular input to ingest threat intelligence feeds and trigger automatic responses.
#2. Optimizing Correlation Search Queries (Answer B)
Well-optimized correlation searches reduce query time and false positives.
Benefit: Faster detections # Triggers automated actions in SOAR with minimal delay.
Example: Usingtstatsinstead of raw searches for efficient event detection.
#3. Employing Prebuilt SOAR Playbooks (Answer E)
SOAR playbooks automate security responses based on predefined workflows.
Benefit: Reduces manual effort in phishing response, malware containment, etc.
Example: Automating phishing email analysis using a SOAR playbook that extracts attachments, checks URLs, and blocks malicious senders.
Why Not the Other Options?
#C. Leveraging saved search acceleration - Helps with dashboard performance, but doesn't directly improve automation.#D. Implementing low-latency indexing - Reduces indexing lag but is not a core automation feature.
References & Learning Resources
#Splunk SOAR Automation Guide: https://docs.splunk.com/Documentation/SOAR#Optimizing Correlation Searches in Splunk ES: https://docs.splunk.com/Documentation/ES#Prebuilt SOAR Playbooks for Security Automation: https://splunkbase.splunk.com

78. Frage
What is the primary purpose of correlation searches in Splunk?

A. To identify patterns and relationships between multiple data sources
B. To create dashboards for real-time monitoring
C. To extract and index raw data
D. To store pre-aggregated search results

Antwort: A

Begründung:
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

79. Frage
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SPLK-5002 Prüfungsfragen: https://www.zertpruefung.ch/SPLK-5002_exam.html