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| Section | Weight | Objectives |
|---|---|---|
| Splunk Enterprise Security (ES) Configuration | 20-25% | - ES dashboards and navigation - Incident review and management - ES deployment and architecture - Managing asset and identity correlation - Configuring data inputs and normalization |
| Splunk Enterprise Security Administration | 10-15% | - ES upgrade and maintenance - ES content management - User management and authentication - Backup and recovery procedures - Performance tuning and optimization |
| Threat Detection and Hunting | 25-30% | - Search and detection frameworks - Using Splunk ES threat intelligence - Proactive threat hunting methodologies - Adversarial tactics, techniques, and procedures (ATT&CK) - Creating and modifying detections - Notable events and risk analysis |
| Splunk SOAR for Security Automation | 10-15% | - SOAR and ES integration - Creating and managing playbooks - Automation workflows and integrations - SOAR platform fundamentals - Incident response automation |
| Incident Response and Investigation | 20-25% | - Container and cloud environment investigation - Incident response workflows - Investigation best practices - Timeline reconstruction - Malware analysis and forensics - Using correlation searches for investigation |
| Security Operations Center (SOC) Fundamentals | 10-15% | - SOC roles and responsibilities - Security monitoring concepts - SIEM architecture in Splunk - Alert triage workflow |
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NEW QUESTION # 82
A threat actor group has begun a campaign that is relevant to an organization. How can the organization's engineer raise the risk score for corresponding intelligence matches in the applicable threat collection?
Answer: A
Explanation:
In Splunk Enterprise Security, increasing the threat collection weight raises the resulting risk score for any indicators matched from that collection. This allows the organization to prioritize intelligence associated with active or relevant threat actor campaigns.
NEW QUESTION # 83
How can an engineer verify if results will return for a potential detection based on historical events within the organization?
Answer: A
Explanation:
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.
NEW QUESTION # 84
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?
Answer: A
Explanation:
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.
NEW QUESTION # 85
How can Splunk engineers monitor indexing performance effectively?(Choosetwo)
Answer: B,C
Explanation:
Monitoring indexing performance in Splunk is crucial for ensuring efficient data ingestion, search performance, and resource utilization.
Methods to Monitor Indexing Performance Effectively:
Use the Monitoring Console (A)
Provides real-time visibility into indexing performance.
Displays resource utilization, indexing rate, queue health, and disk usage.
Track Indexer Queue Size and Throughput (D)
Monitoring queue sizes prevents indexing bottlenecks.
Ensures data is processed efficiently without delays.
NEW QUESTION # 86
Which of the following traces specific stages of an attack lifecycle?
Answer: A
Explanation:
The Lockheed Martin Cyber Kill Chain traces specific stages of an attack lifecycle, from reconnaissance through actions on objectives. It is widely used to understand, detect, and disrupt adversary behavior at each stage of an intrusion.
NEW QUESTION # 87
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