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Splunk SPLK-5002 시험요강:

주제소개
주제 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.
주제 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.
주제 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.
주제 4
  • 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.
주제 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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최신 Cybersecurity Defense Analyst SPLK-5002 무료샘플문제 (Q103-Q108):

질문 # 103
How can an engineer verify if results will return for a potential detection based on historical events within the organization?

정답：B

설명：
To verify if a potential detection will return results, the engineer should run the detection against production data in the same Splunk instance. This ensures the query is tested against actual historical events from the organization's environment, confirming whether it generates meaningful results.


질문 # 104
In the context of Splunk ' s Common Information Model (CIM), which construct ensures that events from different data sources appear in the applicable data model?

정답：C

설명：
CIM data-model datasets commonly use tags as part of their constraints to identify events belonging to a particular semantic category. Therefore, correctly applying the required tags allows heterogeneous source data to qualify for the applicable CIM dataset.
For example, authentication telemetry may originate from Windows, cloud identity systems, VPN appliances, Linux systems, or other authentication platforms. Their original vendor schemas can differ substantially. CIM provides normalization so those events can participate in a common analytical model. Tags and associated event types help categorize the events so that they meet the constraints of the relevant dataset.
Normalization requires more than tagging alone: fields must also be mapped into expected CIM field names.
However, the question asks which construct ensures events from different sources appear in the applicable data model , and the applicable dataset constraints commonly depend on CIM tags.
Hosts identify systems generating data but do not classify an event into a CIM semantic dataset. Assets provide enrichment rather than dataset membership. Field names normalize event attributes after data is appropriately classified, but they do not replace the tagging mechanism used by dataset constraints.
Study Guide topics: CIM, tags, event types, dataset constraints, data normalization, CIM-compliant ingestion.


질문 # 105
An engineer has been asked to build a new dashboard after an increase in login failures across the organization ' s Microsoft Azure domain. They need to construct a search to only display failed logins for their Azure Active Directory users and create a visualization that will help quickly identify failed logins that originate outside of North America. Which search and visualization type combination will achieve this?

정답：A

설명：
The required combination must satisfy two independent requirements : restrict the dataset to failed Azure Active Directory authentication activity and represent the origin of those events geographically. Option D provides that combination by selecting the failure-oriented Azure AD sign-in data and using geographic- coordinate information with a Cluster Map .
A geographic cluster visualization is appropriate when individual events contain point locations such as latitude and longitude. Multiple sign-in failures originating from the same geographic area can then be grouped visually, making concentrations outside the expected operating region-here, North America- immediately apparent. This is particularly useful for authentication monitoring because a raw table of IP addresses does not provide the same rapid geographic interpretation.
The search must also distinguish failures from successful authentication. Merely plotting all sign-ins would allow large quantities of legitimate activity to obscure the specific anomalous behavior being investigated.
Conversely, choosing an inappropriate geographic visualization for point-coordinate data would not provide the intended presentation.
Study Guide topics: Azure AD authentication data, failed-login filtering, geospatial enrichment, geographic dashboards, Cluster Map visualization, security analytics.


질문 # 106
What is the primary function of a Lean Six Sigma methodology in a security program?

정답：A

설명：
Lean Six Sigma (LSS) is a process improvement methodology used to enhance operational efficiency by reducing waste, eliminating errors, and improving consistency.
Primary Function of Lean Six Sigma in a Security Program:
Improves security operations efficiency by optimizing alert handling, threat hunting, and incident response workflows.
Reduces unnecessary steps in SOC processes, eliminating redundancies in threat detection and response.
Enhances decision-making by using data-driven analysis to improve security metrics and Key Performance Indicators (KPIs).


질문 # 107
What are the benefits of maintaining a detection lifecycle?(Choosetwo)

정답：A,B

설명：
Why Maintain a Detection Lifecycle?
Adetection lifecycleensures that security alerts, correlation searches, and automation playbooks arecontinuously refinedto maintainaccuracy, efficiency, and relevanceagainst modern threats.
#1. Detecting and Eliminating Outdated Searches (Answer A)#Removes unnecessary or redundant correlation searchesthat may slow down performance.#Prevents false positivescaused by outdated detection logic.
#Example:A Splunk ES search for anold malware variantmay no longer be effective # it should be updated to detectnew techniques used by attackers.
#2. Ensuring Detections Remain Relevant to Evolving Threats (Answer C)#Regular updatesensure thatnew MITRE ATT&CK techniquesand threat indicators are included.#Example:If attackers start usingLiving-off- the-Land (LotL) techniques, security teams mustupdate detection rules to identify suspicious PowerShell activity.
Why Not the Other Options?
#B. Scaling the Splunk deployment effectively- Lifecycle management improvesdetection accuracy, notinfrastructure scalability.#D. Automating the deployment of new detection logic- Automation helps, but lifecycle management isabout reviewing and updating detections, not just deployment.
References & Learning Resources
#Detection Management in Splunk ES: https://docs.splunk.com/Documentation/ES#Updating Threat Detections Using MITRE ATT&CK in Splunk: https://attack.mitre.org/resources#Best Practices for SOC Detection Engineering: https://splunkbase.splunk.com


질문 # 108
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