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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
  • 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
  • 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 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
  • 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 (Q20-Q25):

NEW QUESTION # 20
When creating detections, which of the following sequences would result in the most performant SPL query?

Answer: D

Explanation:
The most performant SPL design is to define the base query, minimize the data set as early as possible, combine or summarize the remaining data, perform calculations, and format the final output last.
The critical optimization principle is early reduction of search cardinality. Filtering unnecessary events and fields before expensive aggregation or calculation means downstream commands operate on substantially less data. Once the search has constrained the relevant events, aggregation commands such as stats, tstats, or equivalent summarization reduce the event stream further. Calculations with eval or related functions should then operate on this smaller result set, and display-oriented operations such as table, rename, or final formatting should be performed only after analytical processing is complete.
Option A performs aggregation before minimizing the dataset, potentially requiring unnecessary events to participate in expensive operations. Options C and D perform formatting too early, which does not improve detection execution and can complicate or increase downstream processing.
The supplied study material also emphasizes efficient indexed/accelerated searching such as tstats instead of unnecessarily broad raw-event processing, reinforcing the same performance principle.
Study Guide topics: performant SPL, early filtering, aggregation, stats, tstats, search optimization, detection engineering efficiency.


NEW QUESTION # 21
How can you ensure efficient detection tuning?(Choosethree)

Answer: A,B,C

Explanation:
Ensuring Efficient Detection Tuning in Splunk Enterprise Security
Detection tuning is essential to minimize false positives and improve security visibility.
#1. Perform Regular Reviews of False Positives (A)
Reviewing false positives helps refine detection logic.
Analysts should analyze past alerts and adjust correlation rules.
Example:
Tuning a failed login correlation search to exclude known legitimate admin accounts.
#2. Use Detailed Asset and Identity Information (B)
Enriches detections with asset and user context.
Helps differentiate high-risk vs. low-risk security events.
Example:
A login from an executive's laptop is higher risk than from a test server.
#3. Automate Threshold Adjustments (D)
Dynamic thresholds adjust based on activity baselines.
Reduces false positives while maintaining security coverage.
Example:
A brute-force detection rule dynamically adjusts its alerting threshold based on normal user behavior.
C: Disable correlation searches for low-priority threats # Instead of disabling, adjust the rule sensitivity or lower alert severity.
#Additional Resources:
Splunk Security Essentials: Detection Tuning Guide
Tuning Correlation Searches in Splunk ES


NEW QUESTION # 22
The SOC manager has a desire to measure mean time to acknowledge findings (notable events) in order to meet a desired service level objective. Which two fields can be used to measure this metric?

Answer: B

Explanation:
Mean Time to Acknowledge (MTTA) can be measured using the Status and Owner fields. Status indicates when a notable event moves from a new or unacknowledged state, and Owner identifies which analyst acknowledged the event, allowing calculation of the time taken to respond.


NEW QUESTION # 23
An engineer wants to track and report on all authentication to corporate assets, and wants to prioritize critical assets without significantly increasing the number of findings (notable events) generated. What process could be used to accomplish this goal?

Answer: B

Explanation:
By adding all access attempts to the Risk Index and then increasing the Criticality of critical assets, the engineer ensures all authentication activity is tracked while prioritizing findings involving high-value assets. This approach leverages risk-based alerting without flooding the SOC with unnecessary notable events.


NEW QUESTION # 24
Which of the following is not a type of metadata that can be returned by the metadata command?

Answer: B

Explanation:
The metadata command in Splunk can return information about sourcetypes, hosts, and sources, but it does not return data about assets. Assets are managed separately in Enterprise Security's asset and identity framework, not through the metadata command.


NEW QUESTION # 25
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