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| Certification Vendor: | Splunk |
|---|---|
| Exam Name: | Splunk Certified Cybersecurity Defense Engineer |
| Exam Number: | SPLK-5002 |
| Real Exam Qty: | 82 |
| Available Languages: | English |
| Passing Score: | 65-70% (variable) |
| Exam Duration: | 120 minutes |
| Related Certifications: | Splunk Enterprise Security Certified Admin Splunk SOAR Certified Automation Developer Splunk Core Certified User |
| Certificate Validity Period: | 3 years |
| Exam Price: | $200 USD |
| Exam Format: | Multiple choice, Multiple select, Hands-on lab simulation |
| 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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NEW QUESTION # 100
What is the primary function of summary indexing in Splunk reporting?
Answer: C
Explanation:
Primary Function of Summary Indexing in Splunk Reporting
Summary indexing allows pre-aggregation of data to improve performance and speed up reports.
#Why Use Summary Indexing?
Reduces processing time by storing computed results instead of raw data.
Helps SOC teams generate reports faster and optimize search performance.
Example:
Instead of searching millions of firewall logs in real-time, a summary index stores daily aggregated counts of blocked IPs.
#Incorrect Answers:
A: Storing unprocessed log data # Raw logs are stored in primary indexes, not summary indexes.
C: Normalizing raw data for analysis # Normalization is handled by CIM and data models.
D: Enhancing the accuracy of alerts # Summary indexing improves reporting performance, not alert accuracy.
#Additional Resources:
Splunk Summary Indexing Guide
Optimizing SIEM Reports in Splunk
NEW QUESTION # 101
Which REST API method is used to retrieve data from a Splunk index?
Answer: A
Explanation:
The GET method in the Splunk REST API is used to retrieve data from a Splunk index. It allows users and automated scripts to fetch logs, alerts, or query results programmatically.
Key Points About GET in Splunk API:
Used for searching and retrieving logs from indexes.
Can be used to get search results, job status, and Splunk configuration details.
Common API endpoints include:
/services/search/jobs/{search_id}/results- Retrieves results of a completed search.
/services/search/jobs/export- Exports search results in real-time.
NEW QUESTION # 102
Which REST call will show a list of alerts with their specific commands, app, and title?
Answer: D
Explanation:
The correct REST endpoint to list alerts along with their commands, app, and title is:
| rest /servicesNS/user/-/alerts/alert_actions
| table title, eai:acl.app, label, payload_format, command
This query accesses alert actions in the context of the current user and retrieves the specified fields for reporting or inspection.
NEW QUESTION # 103
Which type of correlation search reviews the events in the risk index and uses an aggregation of events impacting a single risk object to generate risk notables?
Answer: A
Explanation:
A Risk Incident Rule correlation search reviews the events stored in the risk index and aggregates them by risk object (such as a user or asset). When the combined risk score crosses a defined threshold, it generates a risk notable in Enterprise Security.
NEW QUESTION # 104
Which type of correlation search reviews the events in the risk index and uses an aggregation of events impacting a single risk object to generate risk notables?
Answer: A
Explanation:
A Risk Incident Rule evaluates accumulated events in the risk index and determines when the combined risk associated with a particular risk object warrants escalation into an analyst-facing finding or notable.
This is a core component of Risk-Based Alerting. Individual detections can create risk events rather than immediately generating separate findings. Each event can contain a risk score, risk object, risk object type, annotations, and contextual information. A Risk Incident Rule then analyzes those events collectively. For example, a user may accumulate several moderate-risk behaviors-an unusual authentication, suspicious process activity, and anomalous access. Individually, each event may be insufficient for escalation; together, they can exceed the aggregation logic defined by the Risk Incident Rule.
This architecture significantly reduces alert fatigue because the SOC evaluates meaningful combinations of evidence rather than every low-confidence event independently.
"Risk Category" is not the correlation-search mechanism performing this aggregation. A generic "Risk Rule" does not identify the specific Enterprise Security construct being tested, and "Risk Incident Notable" describes an outcome rather than the rule evaluating risk-index activity.
Study Guide topics: Risk-Based Alerting, Risk Incident Rules, risk index, risk objects, risk aggregation, finding generation.
NEW QUESTION # 105
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