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| Section | Weight | Objectives |
|---|---|---|
| Building Effective Security Processes and Programs | 20% | - Risk and detection prioritization methodologies - Threat intelligence research, integration and development - Documentation and standard operating procedures development |
| Detection Engineering | 40% | - Risk-based modifiers and detections - Creation and tuning of detections and correlation searches - Generating effective Notable Events and findings - Incorporating context into detections - Detection lifecycle management |
| Auditing and Reporting on Security Programs | 10% | - Dashboard building for program analytics - Security report creation and population - Security metrics development and optimization |
| Data Engineering | 10% | - Data normalization methods and application - Data review and analysis - Performant data indexing creation and maintenance |
| Automation and Efficiency | 20% | - Case management optimization - Response automation using SOAR playbooks - Automation and orchestration for standard operating procedures - REST API usage and description - Integration and automation capability comparison between Enterprise Security and SOAR |
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NEW QUESTION # 12
Which of the following should an engineer do as they evaluate their Threat Detection and Incident Response lifecycle?
Answer: A
NEW QUESTION # 13
A security engineer is tasked with improving threat intelligence sharing within the company.
Whatis the most effective first step?
Answer: B
Explanation:
Improving Threat Intelligence Sharing in an Organization
Threat intelligence enhances cybersecurity by providing real-time insights into emerging threats.
#1. Implement a Real-Time Threat Feed Integration (A)
Enables real-time ingestion of threat indicators (IOCs, IPs, hashes, domains).
Helps automate threat detection and blocking.
Example:
Integrating STIX/TAXII, Splunk Threat Intelligence Framework, or a SOAR platform for live threat updates.
#Incorrect Answers:
B: Restrict access to external threat intelligence sources # Sharing intelligence enhances security, not restricting it.
C: Share raw threat data with all employees # Raw intelligence needs analysis and context before distribution.
D: Use threat intelligence only for executive reporting # SOC analysts, incident responders, and IT teams need actionable intelligence.
#Additional Resources:
Splunk Threat Intelligence Framework
How to Integrate STIX/TAXII in Splunk
NEW QUESTION # 14
Consider the following series of events:
4:00 GMT Detection runs for interval 3:30-4:00
4:30 GMT Detection runs for interval 4:00-4:30
4:35 GMT Event 1 occurs on an endpoint
4:45 GMT Event 1 is indexed
5:00 GMT Detection runs for interval 4:30-5:00
5:05 GMT Event 1 finding is added to ES with timestamp 4:35
5:24 GMT Event 2 occurs on an endpoint
5:30 GMT Detection runs for interval 5:00-5:30
5:35 GMT Event 2 is indexed
6:00 GMT Detection runs for interval 5:30-6:00
What is the problem with the detection schedule chosen and how can it be solved?
Answer: A
Explanation:
The issue is ingestion latency . Event 2 occurs at 5:24 but is not indexed until 5:35. The 5:30 scheduled search covers event time 5:00-5:30, but the event is unavailable when that search executes. By the next execution at 6:00, the search window has advanced to 5:30-6:00, so an event timestamped 5:24 can fall outside the new window even though it is now searchable.
The solution is to increase the detection ' s lookback window sufficiently to accommodate expected indexing delay. Operationally, scheduled detections frequently use overlapping windows-for example, executing every 30 minutes while looking back farther than 30 minutes-to prevent late-arriving events from being missed. Appropriate deduplication or throttling can then address repeated matches caused by overlap.
Decreasing the time window would make the latency problem worse. The scenario also does not indicate that an excessively large window is causing duplicate alerts; it demonstrates a late-arriving event that misses the search interval.
Study Guide topics: detection scheduling, ingestion latency, event time versus index time, lookback windows, late-arriving telemetry.
NEW QUESTION # 15
What is an essential step in building effective dashboards for program analytics?
Answer: D
Explanation:
Building Effective Dashboards for Program Analytics
Well-designed dashboards help SOC teams visualize security trends, performance metrics, and compliance adherence efficiently.
#1. Applying Accelerated Data Models for Better Performance (B)
Speeds up dashboard loading times by using pre-aggregated datasets.
Improves SIEM performance when analyzing large volumes of security logs.
Example:
Instead of running a full search, an accelerated data model pre-indexes event counts by severity level.
#Incorrect Answers:
A: Using predefined templates without modification # Dashboards should be customized for security needs.
C: Avoiding the use of filters and tokens # Filters improve usability by allowing analysts to refine searches.
D: Limiting the number of visualizations # Dashboards should balance performance and visibility rather than limit insights.
#Additional Resources:
Splunk Accelerated Data Models
Building Fast and Efficient Dashboards
NEW QUESTION # 16
Which of the following cURL commands would allow an engineer to effectively disable the REST API endpoint they've been utilizing for testing a detection named TestSearchDevelopment?
Answer: B
Explanation:
To disable a saved search (detection) via the Splunk REST API, the correct syntax is a POST request to the .../disable endpoint. Thus, the proper cURL command is curl -k -u admin:pass
https://localhost:8089/servicesNS/admin/search/saved/searches/TestSearchDevelopment/disable
-X POST
NEW QUESTION # 17
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