Latest SPLK-5002 Braindumps Files, SPLK-5002 Valid Exam Tutorial

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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	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 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.
Topic 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 Certified Cybersecurity Defense Engineer Sample Questions (Q34-Q39):

NEW QUESTION # 34
A company wants to implement risk-based detection for privileged account activities.
Whatshould they configure first?

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

Answer: D

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 # 35
What is the primary function of summary indexing in Splunk reporting?

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

Answer: C

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 # 36
What are the essential components of risk-based detections in Splunk?

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

Answer: B

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 # 37
During a high-priority incident, a user queries an index but sees incomplete results.
Whatis the most likely issue?

A. The search head configuration is outdated.
B. Data normalization was not applied.
C. Indexers have reached their queue capacity.
D. Buckets in the warm state are inaccessible.

Answer: C

Explanation:
If a user queries an index during a high-priority incident but sees incomplete results, it is likely that the indexers are overloaded, causing queue bottlenecks.
Why Indexer Queue Capacity Issues Cause Incomplete Results:
When indexing queues fill up, incoming data cannot be processed efficiently.
Search results may be incomplete or delayed if events are still in the indexing queue and not fully written to disk.
Heavy search loads during incidents can also increase pressure on indexers.
How to Fix It:
Monitor indexing queues via the Monitoring Console (indexing>indexing performance).
Checkmetrics.logon indexers formax_queue_size_exceededwarnings.
Increase indexer capacity or optimize search scheduling to reduce load.

NEW QUESTION # 38
A company wants to create a dashboard that displays normalized event data from various sources.
Whatapproach should they use?

A. Apply search-time field extractions.
B. Configure a summary index.
C. Use SPL queries to manually extract fields.
D. Implement a data model using CIM.

Answer: D

Explanation:
When organizations need to normalize event data from various sources, using Common Information Model (CIM) in Splunk is the best approach.
Why Use CIM for Normalized Event Data?
Standardizes Data Across Different Log Sources
CIM ensures consistent field names and formats across varied log types.
Makes searches, reports, and dashboards easier to manage.
Enables Faster and More Efficient Searches
Uses Data Models to accelerate search queries.
Reduces the need for custom field extractions.

NEW QUESTION # 39
......

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Latest SPLK-5002 Braindumps Files, SPLK-5002 Valid Exam Tutorial

Splunk SPLK-5002 Exam Syllabus Topics:

SPLK-5002 Valid Exam Tutorial & SPLK-5002 Latest Real Exam

Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q34-Q39):

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