SPLK-5002 Latest Guide Files | Fresh SPLK-5002 Dumps

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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	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.
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	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.

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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q36-Q41):

NEW QUESTION # 36
A company wants to implement risk-based detection for privileged account activities.
Whatshould they configure first?

A. Event sampling for raw data
B. Asset and identity information for privileged accounts
C. Correlation searches with low thresholds
D. Automated dashboards for all accounts

Answer: B

Explanation:
Why Configure Asset & Identity Information for Privileged Accounts First?
Risk-based detection focuses on identifying and prioritizing threats based on the severity of their impact. For privileged accounts (admins, domain controllers, finance users), understanding who they are, what they access, and how they behave is critical.
#Key Steps for Risk-Based Detection in Splunk ES:1##Define Privileged Accounts & Groups - Identify high- risk users (Admin, HR, Finance, CISO).2##Assign Risk Scores - Apply higher scores to actions involving privileged users.3##Enable Identity & Asset Correlation - Link users to assets for better detection.
4##Monitor for Anomalies - Detect abnormal login patterns, excessive file access, or unusual privilege escalation.
#Example in Splunk ES:
A domain admin logs in from an unusual location # Trigger high-risk alert A finance director downloads sensitive payroll data at midnight # Escalate for investigation Why Not the Other Options?
#B. Correlation searches with low thresholds - May generate excessive false positives, overwhelming the SOC.#C. Event sampling for raw data - Doesn't provide context for risk-based detection.#D. Automated dashboards for all accounts - Useful for visibility, but not the first step for risk-based security.
References & Learning Resources
#Splunk ES Risk-Based Alerting (RBA): https://www.splunk.com/en_us/blog/security/risk-based-alerting.
html#Privileged Account Monitoring in Splunk: https://docs.splunk.com/Documentation/ES/latest/User
/RiskBasedAlerting#Implementing Privileged Access Security (PAM) with Splunk: https://splunkbase.splunk.
com

NEW QUESTION # 37
A company's Splunk setup processes logs from multiple sources with inconsistent field naming conventions.
Howshould the engineer ensure uniformity across data for better analysis?

A. Apply Common Information Model (CIM) data models for normalization.
B. Use data model acceleration for real-time searches.
C. Configure index-time data transformations.
D. Create field extraction rules at search time.

Answer: A

Explanation:
Why Use CIM for Field Normalization?
When processing logs from multiple sources with inconsistent field names, the best way to ensure uniformity is to use Splunk's Common Information Model (CIM).
#Key Benefits of CIM for Normalization:
Ensures that different field names (e.g., src_ip, ip_src, source_address) are mapped to a common schema.
Allows security teams to run a single search query across multiple sources without manual mapping.
Enables correlation searches in Splunk Enterprise Security (ES) for better threat detection.
Example Scenario in a SOC:
#Problem: The SOC team needs to correlate firewall logs, cloud logs, and endpoint logs for failed logins.
#Without CIM: Each log source uses a different field name for failed logins, requiring multiple search queries.
#With CIM: All failed login events map to the same standardized field (e.g., action="failure"), allowing one unified search query.
Why Not the Other Options?
#A. Create field extraction rules at search time - Helps with parsing data but doesn't standardize field names across sources.#B. Use data model acceleration for real-time searches - Accelerates searches but doesn't fix inconsistent field naming.#D. Configure index-time data transformations - Changes fields at indexing but is less flexible than CIM's search-time normalization.
References & Learning Resources
#Splunk CIM for Normalization: https://docs.splunk.com/Documentation/CIM#Splunk ES CIM Field Mappings: https://splunkbase.splunk.com/app/263#Best Practices for Log Normalization: https://www.splunk.
com/en_us/blog/tips-and-tricks

NEW QUESTION # 38
What is the role of aggregation policies in correlation searches?

A. To index events from multiple sources
B. To group related notable events for analysis
C. To automate responses to critical events
D. To normalize event fields for dashboards

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 # 39
What is the primary function of summary indexing in Splunk reporting?

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

Answer: D

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 # 40
Which Splunk feature enables integration with third-party tools for automated response actions?

A. Workflow actions
B. Event sampling
C. Data model acceleration
D. Summary indexing

Answer: A

Explanation:
Security teams use Splunk Enterprise Security (ES) and Splunk SOAR to integrate with firewalls, endpoint security, and SIEM tools for automated threat response.
#Workflow Actions (B) - Key Integration Feature
Allows analysts to trigger automated actions directly from Splunk searches and dashboards.
Can integrate with SOAR playbooks, ticketing systems (e.g., ServiceNow), or firewalls to take action.
Example:
Block an IP on a firewall from a Splunk dashboard.
Trigger a SOAR playbook for automated threat containment.
#Incorrect Answers:
A: Data Model Acceleration # Speeds up searches, but doesn't handle integrations.
C: Summary Indexing # Stores summarized data for reporting, not automation.
D: Event Sampling # Reduces search load, but doesn't trigger automated actions.
#Additional Resources:
Splunk Workflow Actions Documentation
Automating Response with Splunk SOAR

NEW QUESTION # 41
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SPLK-5002 LATEST GUIDE FILES | FRESH SPLK-5002 DUMPS

SPLK-5002 Latest Guide Files | Fresh SPLK-5002 Dumps