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| Section | Weight | Objectives |
|---|---|---|
| Detection Engineering | 40% | - Detection lifecycle management - Incorporating context into detections - Generating effective Notable Events and findings - Creation and tuning of detections and correlation searches - Risk-based modifiers and detections |
| Building Effective Security Processes and Programs | 20% | - Documentation and standard operating procedures development - Risk and detection prioritization methodologies - Threat intelligence research, integration and development |
| Auditing and Reporting on Security Programs | 10% | - Dashboard building for program analytics - Security report creation and population - Security metrics development and optimization |
| Automation and Efficiency | 20% | - REST API usage and description - Case management optimization - Response automation using SOAR playbooks - Integration and automation capability comparison between Enterprise Security and SOAR - Automation and orchestration for standard operating procedures |
| Data Engineering | 10% | - Data normalization methods and application - Data review and analysis - Performant data indexing creation and maintenance |
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NEW QUESTION # 18
Which search command was used to generate the result in the image below?
Answer: C
Explanation:
The command is datamodel . The exhibit shows structured information describing the Authentication Data Model , including fields such as description, displayName, modelName, objectNameList, objectSummary, and objects. This type of output is characteristic of the Splunk datamodel search command, which can return metadata and structural information about configured data models.
A representative search is:
| datamodel Authentication
The command allows engineers to inspect data-model definitions and understand the objects or datasets that compose a model. This is particularly useful when validating CIM-related configuration, determining available datasets, and developing searches that rely on normalized data.
The metadata command instead returns indexed metadata concerning hosts, sources, or sourcetypes and would not produce the data-model definition structure visible in the exhibit. datatype is not the appropriate Splunk search command for inspecting data-model definitions, and cim is not the command represented by this output.
The visible values description: Authentication Data Model, displayName: Authentication, and modelName:
Authentication are the strongest indicators that the command queried a Splunk data model.
Study Guide topics: Data Models, Common Information Model (CIM), datamodel command, Authentication Data Model, dataset inspection, normalized security data.
NEW QUESTION # 19
Which of the following identifies elements of the Detection Development Lifecyle (DDLC)?
Answer: A
Explanation:
The Detection Development Lifecycle (DDLC) includes the stages Design, Develop, Deploy, Monitor, and Maintain. This structured process ensures detections are thoughtfully built, effectively deployed, and continuously refined for accuracy and relevance.
NEW QUESTION # 20
During a ransomware attack, an adversary might add a default user and password in registry, modify the wallpaper, and create bulk ransomware notes across multiple machines. What is Splunk's method for grouping these types of detections together?
Answer: A
Explanation:
Splunk uses Analytic Stories to group related detections together that align with a specific threat scenario, such as ransomware. These stories provide a collection of correlation searches, baselines, and contextual guidance to detect, investigate, and respond to adversary behaviors.
NEW QUESTION # 21
What is the primary function of a Lean Six Sigma methodology in a security program?
Answer: A
Explanation:
Lean Six Sigma (LSS) is a process improvement methodology used to enhance operational efficiency by reducing waste, eliminating errors, and improving consistency.
Primary Function of Lean Six Sigma in a Security Program:
Improves security operations efficiency by optimizing alert handling, threat hunting, and incident response workflows.
Reduces unnecessary steps in SOC processes, eliminating redundancies in threat detection and response.
Enhances decision-making by using data-driven analysis to improve security metrics and Key Performance Indicators (KPIs).
NEW QUESTION # 22
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: B
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 # 23
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