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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security Automation (SOAR) | 30% | - Incident response automation and orchestration - Playbook design and automation workflows |
| Topic 2: Security Operations and Program Development | 20% | - SOC process design and operational workflows - Threat intelligence integration |
| Topic 3: Data Engineering | 10% | - Data ingestion and onboarding - Indexing performance and management - Data parsing, normalization, and CIM alignment |
| Topic 4: Detection Engineering | 40% | - Detection enrichment with context and risk-based alerting - Creation and tuning of detections (Correlation Searches) - Notable event generation and lifecycle management |
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質問 # 35
Which search command was used to generate the result in the image below?
正解：D
解説：
The result in the image shows details of the Authentication Data Model (description, displayName, modelName, objectNameList, etc.). This output is generated by the datamodel search command, which is used to list and inspect available data models in Splunk.
質問 # 36
An EDR tool was recently purchased and needs to be integrated into existing Splunk SOAR playbooks. Which actions are typically associated with this type of asset?
正解：B
解説：
EDR platforms commonly support host-level actions such as blocking malicious hashes, stopping or blocking processes, quarantining infected endpoints, and retrieving indicators for investigation.
質問 # 37
In Enterprise Security, what is the name of the threat intelligence lookup pertaining to files?
正解：C
解説：
In Splunk Enterprise Security, the file_intel lookup is used for threat intelligence related to files, such as file hashes or suspicious file indicators. This lookup allows correlation searches and risk scoring to incorporate known malicious file information.
質問 # 38
Which configurations are required for data normalization in Splunk?(Choosetwo)
正解：B、C
解説：
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
質問 # 39
During a high-priority incident, a user queries an index but sees incomplete results.
Whatis the most likely issue?
正解：C
解説：
If a user queries an index during a high-priority incident but sees incomplete results, it is likely that the indexers are overloaded, causing queue bottlenecks.
Why Indexer Queue Capacity Issues Cause Incomplete Results:
When indexing queues fill up, incoming data cannot be processed efficiently.
Search results may be incomplete or delayed if events are still in the indexing queue and not fully written to disk.
Heavy search loads during incidents can also increase pressure on indexers.
How to Fix It:
Monitor indexing queues via the Monitoring Console (indexing>indexing performance).
Checkmetrics.logon indexers formax_queue_size_exceededwarnings.
Increase indexer capacity or optimize search scheduling to reduce load.
質問 # 40
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