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| Certification Vendor: | Splunk |
|---|---|
| Exam Name: | Splunk Certified Cybersecurity Defense Engineer |
| Exam Number: | SPLK-5002 |
| Exam Format: | Hands-on lab simulation, Multiple select, Multiple choice |
| Exam Price: | $200 USD |
| Real Exam Qty: | 82 |
| Exam Duration: | 120 minutes |
| Passing Score: | 65-70% (variable) |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Related Certifications: | Splunk Enterprise Security Certified Admin Splunk Core Certified User Splunk SOAR Certified Automation Developer |
| 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 |
>> SPLK-5002 Exam Objectives <<
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NEW QUESTION # 21
What provides consistency for data mapping applied to data model and saved search exports between Splunk Enterprise Security and Splunk SOAR?
Answer: D
Explanation:
Global field mappings provide a consistent mapping layer when data is exported from Enterprise Security data models or saved searches into Splunk SOAR. The objective is to ensure that semantically equivalent values are represented consistently regardless of which detection, search, or data model produced the source event.
This becomes important when SOAR receives security events from multiple searches. One source might expose an endpoint as dest, another as host, and another might use a product-specific field. Consistent global mapping allows downstream SOAR workflows to operate on standardized field semantics instead of requiring every playbook to understand every upstream schema variation.
A field alias is a Splunk knowledge object that can make one indexed or extracted field available under another name during search processing, but that is not the cross-export mapping mechanism requested here.
"Field labels" likewise do not establish the global ES-to-SOAR translation layer. The important clue is the requirement for consistency across both data-model and saved-search exports , which implies a centrally applied mapping configuration.
This design reduces duplicated transformation logic and improves the portability and reliability of automated response workflows.
Study Guide topics: Global field mappings, Enterprise Security-to-SOAR integration, data normalization, event export, automation data consistency.
NEW QUESTION # 22
MITRE D3FEND is designed to compliment MITRE's list of adversarial tactics, techniques, and common knowledge (ATT&CK). Which tactics are associated with MITRE D3FEND in order to detect, deny, and disrupt adversarial efforts?
Answer: A
Explanation:
MITRE D3FEND provides defensive tactics that complement MITRE ATT&CK. The associated tactics are Harden, Detect, Isolate, Deceive, and Evict, which map to defensive measures organizations can use to counter adversarial behaviors.
NEW QUESTION # 23
What must be configured as a setting in a correlation search for a notable to be generated?
Answer: B
Explanation:
A correlation search must have the appropriate Adaptive Response Action configured when its intended outcome is creation of a notable event. Consequently, option C is correct.
The correlation search itself defines the analytics used to identify suspicious activity. Running that search successfully does not, by itself, mean every result automatically becomes a notable. The response configuration determines what Enterprise Security should do after the detection conditions are satisfied.
Configuring the notable-related adaptive response action supplies that operational behavior.
This separation is important because the same detection framework can support different outcomes.
Depending on design requirements, a correlation search may create analyst-facing findings, generate risk, invoke another response mechanism, or participate in additional automated workflows. The detection logic and response behavior therefore represent distinct parts of the engineering process.
A SOAR playbook is not a prerequisite for generating a notable; SOAR normally operates as a subsequent orchestration or response capability. Likewise, appending a | notable command to the SPL is not the configuration requirement being tested by this question.
Study Guide topics: Enterprise Security correlation searches, notable generation, Adaptive Response Actions, detection outcomes, response configuration.
NEW QUESTION # 24
What is the primary purpose of data indexing in Splunk?
Answer: C
Explanation:
Understanding Data Indexing in Splunk
In Splunk Enterprise Security (ES) and Splunk SOAR, data indexing is a fundamental process that enables efficient storage, retrieval, and searching of data.
Why is Data Indexing Important?
Stores raw machine data (logs, events, metrics) in a structured manner. Enables fast searching through optimized data storage techniques. Uses an indexer to process, compress, and store data efficiently.
Why the Correct Answer is B?
Splunk indexes data to store it efficiently while ensuring fast retrieval for searches, correlation searches, and analytics.
It assigns metadata to indexed events, allowing SOC analysts to quickly filter and search logs.
NEW QUESTION # 25
An engineer observes a high volume of false positives generated by a correlation search.
Whatsteps should they take to reduce noise without missing critical detections?
Answer: C
Explanation:
How to Reduce False Positives in Correlation Searches?
High false positives can overwhelm SOC teams, causing alert fatigue and missed real threats. The best solution is to fine-tune suppression rules and refine thresholds.
#How Suppression Rules & Threshold Tuning Help:#Suppression Rules: Prevent repeated false positives from low-risk recurring events (e.g., normal system scans).#Threshold Refinement: Adjust sensitivity to focus on true threats (e.g., changing a login failure alert from 3 to 10 failed attempts).
#Example in Splunk ES:#Scenario: A correlation search generates too many alerts for failed logins.#Fix: SOC analysts refine detection thresholds:
Suppress alerts if failed logins occur within a short timeframe but are followed by a successful login.
Only trigger an alert if failed logins exceed 10 attempts within 5 minutes.
Why Not the Other Options?
#A. Increase the frequency of the correlation search - Increases search load without reducing false positives.
#C. Disable the correlation search temporarily - Leads to blind spots in detection.#D. Limit the search to a single index - May exclude critical security logs from detection.
References & Learning Resources
#Splunk ES Correlation Search Optimization Guide: https://docs.splunk.com/Documentation/ES#Reducing False Positives in SOC Workflows: https://splunkbase.splunk.com#Fine-Tuning Security Alerts in Splunk:
https://www.splunk.com/en_us/blog/security
NEW QUESTION # 26
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