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Splunk SPLK-5002 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 2	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.
Topic 3	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.
Topic 4	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.
Topic 5	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.

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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q64-Q69):

NEW QUESTION # 64
What is the main purpose of Splunk's Common Information Model (CIM)?

A. To create accelerated reports
B. To compress data during indexing
C. To extract fields from raw events
D. To normalize data for correlation and searches

Answer: D

Explanation:
What is the Splunk Common Information Model (CIM)?
Splunk's Common Information Model (CIM) is a standardized way to normalize and map event data from different sources to a common field format. It helps with:
Consistent searches across diverse log sources
Faster correlation of security events
Better compatibility with prebuilt dashboards, alerts, and reports
Why is Data Normalization Important?
Security teams analyze data from firewalls, IDS/IPS, endpoint logs, authentication logs, and cloud logs.
These sources have different field names (e.g., "src_ip" vs. "source_address").
CIM ensures a standardized format, so correlation searches work seamlessly across different log sources.
How CIM Works in Splunk?
#Maps event fields to a standardized schema#Supports prebuilt Splunk apps like Enterprise Security (ES)
#Helps SOC teams quickly detect security threats
#Example Use Case:
A security analyst wants to detect failed admin logins across multiple authentication systems.
Without CIM, different logs might use:
user_login_failed
auth_failure
login_error
With CIM, all these fields map to the same normalized schema, enabling one unified search query.
Why Not the Other Options?
#A. Extract fields from raw events - CIM does not extract fields; it maps existing fields into a standardized format.#C. Compress data during indexing - CIM is about data normalization, not compression.#D. Create accelerated reports - While CIM supports acceleration, its main function is standardizing log formats.
References & Learning Resources
#Splunk CIM Documentation: https://docs.splunk.com/Documentation/CIM#How Splunk CIM Helps with Security Analytics: https://www.splunk.com/en_us/solutions/common-information-model.html#Splunk Enterprise Security & CIM Integration: https://splunkbase.splunk.com/app/263

NEW QUESTION # 65
Which configurations are required for data normalization in Splunk?(Choosetwo)

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

Answer: C,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 # 66
Which components are necessary to develop a SOAR playbook in Splunk?(Choosethree)

A. Threat intelligence feeds
B. Manual approval processes
C. Defined workflows
D. Actionable steps or tasks
E. Integration with external tools

Answer: C,D,E

Explanation:
Splunk SOAR (Security Orchestration, Automation, and Response) playbooks automate security processes, reducing response times.
#1. Defined Workflows (A)
A structured flowchart of actions for handling security events.
Ensures that the playbook follows a logical sequence (e.g., detect # enrich # contain # remediate).
Example:
If a phishing email is detected, the workflow includes:
Extract email artifacts (e.g., sender, links).
Check indicators against threat intelligence feeds.
Quarantine the email if it is malicious.
#2. Actionable Steps or Tasks (C)
Each playbook contains specific, automated steps that execute responses.
Examples:
Extracting indicators from logs.
Blocking malicious IPs in firewalls.
Isolating compromised endpoints.
#3. Integration with External Tools (E)
Playbooks must connect with SIEM, EDR, firewalls, threat intelligence platforms, and ticketing systems.
Uses APIs and connectors to integrate with tools like:
Splunk ES
Palo Alto Networks
Microsoft Defender
ServiceNow
#Incorrect Answers:
B: Threat intelligence feeds # These enrich playbooks but are not mandatory components of playbook development.
D: Manual approval processes # Playbooks are designed for automation, not manual approvals.
#Additional Resources:
Splunk SOAR Playbook Documentation
Best Practices for Developing SOAR Playbooks

NEW QUESTION # 67
What are the essential components of risk-based detections in Splunk?

A. Summary indexing, tags, and event types
B. Source types, correlation searches, and asset groups
C. Risk modifiers, risk objects, and risk scores
D. Alerts, notifications, and priority levels

Answer: C

Explanation:
What Are Risk-Based Detections in Splunk?
Risk-based detections in Splunk Enterprise Security (ES) assign risk scores to security events based on threat severity and asset criticality.
#Key Components of Risk-Based Detections:1##Risk Modifiers - Adjusts risk scores based on event type (e.
g., failed logins, malware detections).2##Risk Objects - Entities associated with security events (e.g., users, IPs, devices).3##Risk Scores - Numerical values indicating the severity of a risk.
#Example in Splunk Enterprise Security:#Scenario: A high-privilege account (Admin) fails multiple logins from an unusual location.#Splunk ES applies risk-based detection:
Failed logins add +10 risk points
Login from a suspicious country adds +15 points
Total risk score exceeds 25 # Triggers an alert
Why Not the Other Options?
#B. Summary indexing, tags, and event types - Summary indexing stores precomputed data, but doesn't drive risk-based detection.#C. Alerts, notifications, and priority levels - Important, but risk-based detection is based on scoring, not just alerts.#D. Source types, correlation searches, and asset groups - Helps in data organization, but not specific to risk-based detections.
References & Learning Resources
#Splunk ES Risk-Based Alerting Guide: https://docs.splunk.com/Documentation/ES#Risk-Based Detections
& Scoring in Splunk: https://www.splunk.com/en_us/blog/security/risk-based-alerting.html#Best Practices for Risk Scoring in SOC Operations: https://splunkbase.splunk.com

NEW QUESTION # 68
Which methodology prioritizes risks by evaluating both their likelihood and impact?

A. Incident lifecycle management
B. Threat modeling
C. Risk-based prioritization
D. Statistical anomaly detection

Answer: C

Explanation:
Understanding Risk-Based Prioritization
Risk-based prioritization is a methodology that evaluatesboth the likelihood and impact of risksto determine which threats require immediate action.
#Why Risk-Based Prioritization?
Focuses onhigh-impact and high-likelihoodrisks first.
HelpsSOC teams manage alerts effectivelyand avoid alert fatigue.
Used inSIEM solutions (Splunk ES) and Risk-Based Alerting (RBA).
Example in Splunk Enterprise Security (ES):
Afailed login attemptfrom aninternal employeemight below risk(low impact, low likelihood).
Multiple failed loginsfrom aforeign countrywith a knownbad reputationcould behigh risk(high impact, high likelihood).
#Incorrect Answers:
A: Threat modeling# Identifies potential threats but doesn'tprioritize risks dynamically.
C: Incident lifecycle management# Focuses on handling security incidents, notrisk evaluation.
D: Statistical anomaly detection# Detects unusual activity but doesn'tprioritize based on impact.
#Additional Resources:
Splunk Risk-Based Alerting (RBA) Guide
NIST Risk Assessment Framework

NEW QUESTION # 69
......

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Exam SPLK-5002 Dumps - Customizable SPLK-5002 Exam Mode

Splunk SPLK-5002 Exam Syllabus Topics:

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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q64-Q69):

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