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| Certification Vendor: | Splunk |
|---|---|
| Exam Name: | Splunk Certified Cybersecurity Defense Engineer |
| Exam Number: | SPLK-5002 |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 82 |
| Passing Score: | 65-70% (variable) |
| Available Languages: | English |
| Exam Price: | $200 USD |
| Exam Duration: | 120 minutes |
| Related Certifications: | Splunk Core Certified User Splunk Enterprise Security Certified Admin Splunk SOAR Certified Automation Developer |
| Exam Format: | Hands-on lab simulation, Multiple select, Multiple choice |
| Sample Questions: | Splunk SPLK-5002 Sample Questions |
| Exam Way: | Online proctored exam at Pearson VUE testing centers or remote proctoring |
| Pre Condition: | Splunk Core Certified User, Splunk Enterprise Security Certified Admin, and Splunk SOAR Certified Automation Developer recommended; minimum 1-2 years hands-on Splunk security experience strongly advised |
| Official Syllabus URL: | https://www.splunk.com/en_us/training/certification-track/splunk-certified-cybersecurity-defense-engineer.html |
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問題 #46
When creating a case in Splunk SOAR, which action should be taken to correlate various findings (risk notables) to ensure all are actioned?
答案:B
解題說明:
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.
問題 #47
What are key elements of a well-constructed notable event?(Choosethree)
答案:A,B,C
解題說明:
A notable event in Splunk Enterprise Security (ES) represents a significant security detection that requires investigation.
#Key Elements of a Good Notable Event:#Meaningful Descriptions (Answer A) Helps analysts understand the event at a glance.
Example: Instead of "Possible attack detected," use "Multiple failed admin logins from foreign IP address".
#Proper Categorization (Answer C)
Ensures events are classified correctly (e.g., Brute Force, Insider Threat, Malware Activity).
Example: A malicious file download alert should be categorized as "Malware Infection", not just "General Alert".
#Relevant Field Extractions (Answer D)
Ensures that critical details (IP, user, timestamp) are present for SOC analysis.
Example: If an alert reports failed logins, extracted fields should include username, source IP, and login method.
Why Not the Other Options?
#B. Minimal use of contextual data - More context helps SOC analysts investigate faster.
References & Learning Resources
#Building Effective Notable Events in Splunk ES: https://docs.splunk.com/Documentation/ES#SOC Best Practices for Security Alerts: https://splunkbase.splunk.com#How to Categorize Security Alerts Properly:
https://www.splunk.com/en_us/blog/security
問題 #48
A security analyst wants to validate whether a newly deployed SOAR playbook is performing as expected.
Whatsteps should they take?
答案:D
解題說明:
A SOAR (Security Orchestration, Automation, and Response) playbook is a set of automated actions designed to respond to security incidents. Before deploying it in a live environment, a security analyst must ensure that it operates correctly, minimizes false positives, and doesn't disrupt business operations.
#Key Reasons for Using Simulated Incidents:
Ensures that the playbook executes correctly and follows the expected workflow.
Identifies false positives or incorrect actions before deployment.
Tests integrations with other security tools (SIEM, firewalls, endpoint security).
Provides a controlled testing environment without affecting production.
How to Test a Playbook in Splunk SOAR?
1##Use the "Test Connectivity" Feature - Ensures that APIs and integrations work.2##Simulate an Incident - Manually trigger an alert similar to a real attack (e.g., phishing email or failed admin login).3##Review the Execution Path - Check each step in the playbook debugger to verify correct actions.4##Analyze Logs & Alerts - Validate that Splunk ES logs, security alerts, and remediation steps are correct.5##Fine-tune Based on Results - Modify the playbook logic to reduce unnecessary alerts or excessive automation.
Why Not the Other Options?
#B. Monitor the playbook's actions in real-time environments - Risky without prior validation. Itcan cause disruptions if the playbook misfires.#C. Automate all tasks immediately - Not best practice. Gradual deployment ensures better security control and monitoring.#D. Compare with existing workflows - Good practice, but it does not validate the playbook's real execution.
References & Learning Resources
#Splunk SOAR Documentation: https://docs.splunk.com/Documentation/SOAR#Testing Playbooks in Splunk SOAR: https://www.splunk.com/en_us/products/soar.html#SOAR Playbook Debugging Best Practices:
https://splunkbase.splunk.com
問題 #49
Which of the following detections would use a high count of events with Windows Event Code 4740 grouped by a user to determine suspicious behavior?
答案:D
解題說明:
Windows Security Event ID 4740 records the condition "A user account was locked out." Consequently, a detection that counts EventCode 4740 events and aggregates them by user is specifically measuring repeated account-lockout activity. The appropriate detection is therefore Detect Excessive User Account Lockouts .
From a detection-engineering perspective, a useful analytic would establish a baseline or threshold and then aggregate by the affected account, for example conceptually using stats count by user. A high number of lockouts may indicate password spraying, credential-stuffing activity, an incorrectly configured service using stale credentials, or an automated process repeatedly authenticating with an invalid password. Context such as source workstation, account type, time window, and historical frequency would improve fidelity.
The distractors represent different telemetry classes. Excessive successful or failed logins normally involve authentication events such as 4624/4625 rather than 4740. Network-connection detections require network or endpoint connection telemetry, and AWS security scanning is unrelated to Windows account-lockout auditing.
The supplied material presents EventCode 4740 specifically in this detection-selection context on page 3.
Study Guide topics: Windows security telemetry, EventCode-based analytics, aggregation, account lockouts, authentication detections, threshold-based detection engineering.
問題 #50
Which configurations are required for data normalization in Splunk?(Choosetwo)
答案:B,D
解題說明:
Configurations Required for Data Normalization in Splunk
Data normalization ensures consistent field naming and event structuring, especially for Splunk Common Information Model (CIM) compliance.
#1. props.conf (A)
Defines how data is parsed and indexed.
Controls field extractions, event breaking, and timestamp recognition.
Example:
Assigns custom sourcetypes and defines regex-based field extraction.
#2. transforms.conf (B)
Used for data transformation, lookup table mapping, and field aliasing.
Example:
Normalizes firewall logs by renaming src_ip # src to align with CIM.
#Incorrect Answers:
C: savedsearches.conf # Defines scheduled searches, not data normalization.
D: authorize.conf # Manages user permissions, not data normalization.
E: eventtypes.conf # Groups events into categories but doesn't modify data structure.
#Additional Resources:
Splunk Data Normalization Guide
Understanding props.conf and transforms.conf
問題 #51
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