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Splunk SPLK-5002 認定試験の出題範囲：

トピック	出題範囲
トピック 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.
トピック 2	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.
トピック 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.
トピック 4	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.
トピック 5	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.

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Splunk Certified Cybersecurity Defense Engineer 認定 SPLK-5002 試験問題 (Q93-Q98):

質問 # 93
Engineers are commonly asked to turn data sources like EDR alerts into risk events. Doing so requires a dynamic mapping of the signatures in the rule to MITRE ATT&CK. Which of the following fields could be used to dynamically set the MITRE ATT&CK technique ID for the EDR alerts?

A. annotations.mitre_attack.tactic_id
B. mitre_attack.tactic_id
C. mitre_attack.mitre_technique_id
D. annotations.mitre_attack.mitre_technique_id

正解：D

解説：
Risk-based alerting expects MITRE ATT&CK mappings to be provided through the annotations namespace. The correct dynamic field for specifying the ATT&CK technique ID is annotations.mitre_attack.mitre_technique_id, which Splunk uses when generating risk events.

質問 # 94
When creating detections, which of the following sequences would result in the most performant SPL query?

A. Define base query, combine/summarize data, minimize data, execute calculations, format the data
B. Define base query, minimize data, combine/summarize data, format the data, execute calculations
C. Define base query, minimize data, combine/summarize data, execute calculations, format the data
D. Define base query, minimize data, format the data, combine/summarize data, execute calculations

正解：C

解説：
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.

質問 # 95
When creating a case in Splunk SOAR, which action should be taken to correlate various findings (risk notables) to ensure all are actioned?

A. Search Splunk Enterprise Security for all related events based on key fields in a risk notable and select how to process the results to decide which events to merge into the current investigation.
B. Search Splunk Enterprise Security for all related events based on key fields in a notable and select how to process the results to decide which events to merge into the current investigation.
C. Search Splunk Enterprise Security for similar or duplicate events based on the risk_object field in a risk notable.
D. Search Splunk Enterprise Security for similar or duplicate events based on the threat_object field in a risk notable.

正解：A

解説：
The correct approach is to search Enterprise Security for all related events using the significant fields in the risk notable , review those results, and determine which findings should be incorporated into the active investigation. This makes D more complete than simply searching for duplicate values of risk_object or threat_object.
Risk-based detections often aggregate multiple behavioral observations around an entity such as a user, host, or other risk object. A single investigation may therefore involve several risk notables representing different behaviors, techniques, or stages of activity. Correlating only on risk_object can be too restrictive or produce misleading associations because the analyst also needs relevant event context and other identifying fields.
The workflow described by D supports the investigation objective: locate related security events , assess their contextual relationship, and deliberately merge the appropriate findings into the current case so that they are tracked and actioned together.
The uploaded study-guide extract does not contain this exact question, so this selection is based on the Enterprise Security/SOAR case-correlation workflow represented by the terminology in the question.
Study Guide topics: investigation management, risk notables, risk objects, case correlation, SOAR case handling, finding aggregation.

質問 # 96
Which phase of the incident response lifecycle would cause the least amount of friction when replacing manual steps with automation?

A. Remediation
B. Containment
C. Triage
D. Rendering a verdict

正解：C

解説：
Triage involves repetitive, data-gathering, and enrichment steps (e.g., indicator lookups, context collection) that can be automated with minimal risk. This phase typically introduces the least friction when shifting from manual work to automation.

質問 # 97
How can you incorporate additional context into notable events generated by correlation searches?

A. By configuring additional indexers
B. By using the dedup command in SPL
C. By adding enriched fields during search execution
D. By optimizing the search head memory

正解：C

解説：
In Splunk Enterprise Security (ES), notable events are generated by correlation searches, which are predefined searches designed to detect security incidents by analyzing logs and alerts from multiple data sources. Adding additional context to these notable events enhances their value for analysts and improves the efficiency of incident response.
To incorporate additional context, you can:
Use lookup tables to enrich data with information such as asset details, threat intelligence, and user identity.
Leverage KV Store or external enrichment sources like CMDB (Configuration Management Database) and identity management solutions.
Apply Splunk macros or eval commands to transform and enhance event data dynamically.
Use Adaptive Response Actions in Splunk ES to pull additional information into a notable event.
The correct answer is A. By adding enriched fields during search execution, because enrichment occurs dynamically during search execution, ensuring that additional fields (such as geolocation, asset owner, and risk score) are included in the notable event.

質問 # 98
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