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Splunk SPLK-5002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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
  • 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.

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SPLK-5002 Study Questions - SPLK-5002 Guide Torrent & SPLK-5002 Exam Torrent

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Splunk Certified Cybersecurity Defense Engineer Sample Questions (Q44-Q49):

NEW QUESTION # 44
When creating a case in Splunk SOAR, which action should be taken to correlate various findings (risk notables) to ensure all are actioned?

Answer: B

Explanation:
When creating a case in Splunk SOAR, correlation is achieved by searching Splunk Enterprise Security for all related events based on key fields in a risk notable, then deciding how to process and merge those events into the investigation. This ensures that all relevant risk notables are actioned together for a complete response.


NEW QUESTION # 45
An engineer needs to create a new report capturing the vendors and products that detect a particular CVE in their environment. How can they ensure that the search associated with the report only includes accelerated data?

Answer: D

Explanation:
The appropriate approach is to query the Vulnerabilities data model using tstats , constrain the results to the particular CVE, and group or aggregate the results by vendor_product. This satisfies both requirements in the question: selecting vulnerability information associated with a CVE and ensuring that the search operates against accelerated data.
tstats is specifically designed to query indexed fields and accelerated data-model summaries efficiently. In conceptual form, the analytic follows this structure:
| tstats ... from datamodel=Vulnerabilities... where ...cve= < value > by ...vendor_product The exact field prefix depends on the dataset being addressed, but the architectural principle is the same: use the accelerated Vulnerabilities data model rather than scanning raw vulnerability events.
The Updates data model is not the appropriate semantic domain for reporting products associated with identified vulnerabilities. Likewise, simply searching for vendor_product without constraining the requested CVE would not satisfy the report requirement.
This question reinforces a recurring Cybersecurity Defense Engineer theme: choose the correct CIM domain and use accelerated-search mechanisms when operational reporting must scale efficiently.
Study Guide topics: Vulnerabilities data model, tstats, accelerated data, CVE reporting, vendor_product, search optimization.


NEW QUESTION # 46
What is the primary purpose of correlation searches in Splunk?

Answer: C

Explanation:
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


NEW QUESTION # 47
Consider the following series of events:
4:00 GMT Detection runs for interval 3:30-4:00
4:30 GMT Detection runs for interval 4:00-4:30
4:35 GMT Event 1 occurs on an endpoint
4:45 GMT Event 1 is indexed
5:00 GMT Detection runs for interval 4:30-5:00
5:05 GMT Event 1 finding is added to ES with timestamp 4:35
5:24 GMT Event 2 occurs on an endpoint
5:30 GMT Detection runs for interval 5:00-5:30
5:35 GMT Event 2 is indexed
6:00 GMT Detection runs for interval 5:30-6:00
What is the problem with the detection schedule chosen and how can it be solved?

Answer: C

Explanation:
In this scenario, events are indexed after the scheduled detection window has already executed, meaning detections miss relevant events. This happens due to log ingestion delay. The solution is to increase the detection time window (or use a delay offset) so that detections account for delayed logs, ensuring events like Event 1 and Event 2 are included in the proper detection run.


NEW QUESTION # 48
What field is used by default to direct data into CIM data model datasets?

Answer: A

Explanation:
By default, data is directed into CIM (Common Information Model) data model datasets using the tag field. Tags applied to events determine which datasets the events populate, enabling normalization and alignment with CIM.


NEW QUESTION # 49
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