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Splunk SPLK-5002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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 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 (Q21-Q26):

NEW QUESTION # 21
Which of the following traces specific stages of an attack lifecycle?

Answer: A

Explanation:
The Lockheed Martin Cyber Kill Chain traces specific stages of an attack lifecycle, from reconnaissance through actions on objectives. It is widely used to understand, detect, and disrupt adversary behavior at each stage of an intrusion.


NEW QUESTION # 22
Which Splunk feature helps in tracking and documenting threat trends over time?

Answer: B

Explanation:
Why Use Risk-Based Dashboards for Tracking Threat Trends?
Risk-based dashboards in Splunk Enterprise Security (ES) provide a structured way to track threats over time.
#How Risk-Based Dashboards Help:#Aggregate security events into risk scores # Helps prioritize high-risk activities.#Show historical trends of threat activity.#Correlate multiple risk factors across different security events.
#Example in Splunk ES:#Scenario: A SOC team tracks insider threat activity over 6 months.#The Risk-Based Dashboard shows:
Users with rising risk scores over time.
Patterns of malicious behavior (e.g., repeated failed logins + data exfiltration).
Correlation between different security alerts (e.g., phishing clicks # malware execution).
Why Not the Other Options?
#A. Event sampling - Helps with performance optimization, not threat trend tracking.#C. Summary indexing
- Stores precomputed data but is not designed for tracking risk trends.#D. Data model acceleration - Improves search speed, but doesn't track security trends.
References & Learning Resources
#Splunk ES Risk-Based Alerting Guide: https://docs.splunk.com/Documentation/ES#Tracking Security Trends Using Risk-Based Dashboards: https://splunkbase.splunk.com#How to Build Risk-Based Analytics in Splunk: https://www.splunk.com/en_us/blog/security


NEW QUESTION # 23
In order to perform a complete data assessment, an engineer's role within Splunk must have which of the following?

Answer: C

Explanation:
To perform a complete data assessment in Splunk, an engineer must have access to applicable indexes. Without index access, the engineer cannot review ingested data, validate mappings, or evaluate coverage for detections and reporting.


NEW QUESTION # 24
Which of the following should be the primary reference when designing a new playbook in Splunk SOAR?

Answer: D

Explanation:
When designing a new playbook in Splunk SOAR, the existing Standard Operating Procedure (SOP) should be the primary reference. SOPs define the approved steps and workflows for analysts, ensuring that automated playbooks align with organizational processes and compliance requirements.


NEW QUESTION # 25
When building detections using the Authentication Data Model, which values are recommended for use against the action field?

Answer: A

Explanation:
Within the CIM Authentication Data Model , the action field represents the outcome or state of an authentication operation. The recommended normalized values represented by the question are success, failure, pending, and error .
Normalization is critical because authentication technologies use highly variable native terminology. A Windows event may represent an authentication result through one event code, a VPN appliance through another vendor-specific status, and a cloud identity provider through a JSON result field. CIM maps those source-specific outcomes into common semantic values. A detection engineer can therefore write logic such as:
action= " failure "
without separately accounting for every vendor ' s native representation.
allowed and blocked are more naturally associated with access or network-control decisions and do not describe the normalized authentication outcome being tested. Likewise, denied does not replace the CIM- normalized failure value in the answer set.
Consistent use of the expected action vocabulary directly affects detection reliability. Incorrect mappings can cause failed authentications to disappear from CIM-based searches, dashboards, accelerated data-model queries, and threshold detections.
Study Guide topics: Authentication Data Model; CIM; action; normalized authentication outcomes; data mapping; cross-source detection engineering.


NEW QUESTION # 26
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