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| Section | Weight | Objectives |
|---|---|---|
| Security Operations and Program Development | 20% | - SOC process design and operational workflows - Threat intelligence integration |
| Detection Engineering | 40% | - Notable event generation and lifecycle management - Creation and tuning of detections (Correlation Searches) - Detection enrichment with context and risk-based alerting |
| Data Engineering | 10% | - Data ingestion and onboarding - Indexing performance and management - Data parsing, normalization, and CIM alignment |
| Security Automation (SOAR) | 30% | - Playbook design and automation workflows - Incident response automation and orchestration |
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NEW QUESTION # 38
What is the best method to operationalize the results of a threat hunt for daily use by SOC analysts?
Answer: B
Explanation:
The most effective way to operationalize a validated threat-hunting result is to create detections based on the documented findings . Threat hunting is exploratory: analysts search historical or current telemetry for behaviors that may not yet have reliable automated coverage. Once a repeatable malicious or suspicious pattern is identified and validated, detection engineering converts that knowledge into an analytic that operates continuously.
This establishes a mature feedback loop:
Threat hunt # validate behavior # document evidence # engineer detection # test # deploy # monitor and tune.
Reports and communication remain valuable, particularly for management, architecture, and lessons learned, but they do not provide continuous identification of recurrence. A detection allows the SOC to identify the behavior automatically during routine operations and present relevant results to analysts.
The detection should preserve the context learned during the hunt, including useful fields, appropriate time windows, entity information, exclusions, and potentially ATT & CK annotations or risk information.
Engineers should also assess whether the hunting evidence supports a sufficiently reliable analytic to avoid excessive false positives.
Study Guide topics: threat hunting, detection operationalization, detection lifecycle, hunt-to-detection workflow, continuous security monitoring.
NEW QUESTION # 39
What field is used by default to direct data into CIM data model datasets?
Answer: D
Explanation:
By default, data is directed into CIM (Common Information Model) data model datasets using the tag field. Tags applied to events determine which datasets the events populate, enabling normalization and alignment with CIM.
NEW QUESTION # 40
What is a key advantage of using SOAR playbooks in Splunk?
Answer: A
Explanation:
Splunk SOAR (Security Orchestration, Automation, and Response) playbooks help SOC teams automate, orchestrate, and respond to threats faster.
#Key Benefits of SOAR Playbooks
Automates Repetitive Tasks
Reduces manual workload for SOC analysts.
Automates tasks like enriching alerts, blocking IPs, and generating reports.
Orchestrates Multiple Security Tools
Integrates with firewalls, EDR, SIEMs, threat intelligence feeds.
Example: A playbook can automatically enrich an IP address by querying VirusTotal, Splunk, and SIEM logs.
Accelerates Incident Response
Reduces Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR).
Example: A playbook can automatically quarantine compromised endpoints in CrowdStrike after an alert.
#Incorrect Answers:
A: Manually running searches across multiple indexes # SOAR playbooks are about automation, not manual searches.
C: Improving dashboard visualization capabilities # Dashboards are part of SIEM (Splunk ES), not SOAR playbooks.
D: Enhancing data retention policies # Retention is a Splunk Indexing feature, not SOAR-related.
#Additional Resources:
Splunk SOAR Playbook Guide
Automating Threat Response with SOAR
NEW QUESTION # 41
When creating a detection, how might an engineer ensure that all possible contextual fields about a given asset and identity are added to a risk event?
Answer: B
Explanation:
To ensure all possible contextual fields about an asset and identity are included in a risk event, the engineer should include the standard CIM fields (such as user, src, src_user, etc.) in the detection output. These fields are recognized by the Assets & Identities framework and automatically enrich risk events with relevant context.
NEW QUESTION # 42
The Director of Security would like to understand the operational efficiency of the SOC analysts at a high level. What is a metric that can be used to determine their efficiency?
Answer: D
Explanation:
MTTR - Mean Time to Respond/Resolve - is the most appropriate high-level indicator of SOC analyst operational efficiency among the choices provided. It measures how quickly the SOC progresses from identification of an actionable security condition through investigation and response or resolution, depending on the organization ' s specific MTTR definition.
MTTD, or Mean Time to Detect, primarily measures detection capability and telemetry/detection-engineering effectiveness rather than analyst processing efficiency. A strong SOC could have excellent analyst workflows yet still exhibit a high MTTD if telemetry coverage or detection content is weak. MTBR is generally associated with reliability or recurrence-oriented measurements and is not the primary SOC analyst efficiency metric. MTTI can measure investigation duration in some organizations, but MTTR provides the broader executive-level operational indicator requested by the question.
For leadership reporting, MTTR is most useful when segmented by severity, incident class, team, or reporting period; a single aggregate average can otherwise be distorted by extreme cases. The supplied Cybersecurity Defense Engineer material emphasizes measurable SOC lifecycle metrics and distinguishes operational performance indicators from simple activity counts.
Study Guide topics: SOC performance metrics, operational efficiency, MTTR, incident lifecycle measurement, security-program reporting.
NEW QUESTION # 43
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