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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Auditing and Reporting on Security Programs | 10% | - Security report creation and population - Security metrics development and optimization - Dashboard building for program analytics |
| Topic 2: Automation and Efficiency | 20% | - Automation and orchestration for standard operating procedures - REST API usage and description - Case management optimization - Response automation using SOAR playbooks - Integration and automation capability comparison between Enterprise Security and SOAR |
| Topic 3: Building Effective Security Processes and Programs | 20% | - Risk and detection prioritization methodologies - Documentation and standard operating procedures development - Threat intelligence research, integration and development |
| Topic 4: Detection Engineering | 40% | - Detection lifecycle management - Generating effective Notable Events and findings - Incorporating context into detections - Creation and tuning of detections and correlation searches - Risk-based modifiers and detections |
| Topic 5: Data Engineering | 10% | - Performant data indexing creation and maintenance - Data review and analysis - Data normalization methods and application |
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NEW QUESTION # 74
A corporate laptop was disconnected from the internet Friday at 5PM local time. While offline, the user unknowingly opened a malicious file. The laptop came back online the following Monday morning, 9AM local time. The current detection has a 15 minute lookback period. How can the detection be tuned to account for this scenario?
Answer: B
Explanation:
To catch events that occurred while the laptop was offline and only indexed later, the detection should leverage event time rather than index time. Event time ensures detections are based on when the activity actually happened, not when the logs were ingested, preventing missed findings after delayed ingestion.
NEW QUESTION # 75
What is the primary purpose of correlation searches in Splunk?
Answer: A
Explanation:
Correlation searches in Splunk Enterprise Security (ES) are a critical component of Security Operations Center (SOC) workflows, designed to detect threats by analyzing security data from multiple sources.
Primary Purpose of Correlation Searches:
Identify threats and anomalies: They detect patterns and suspicious activity by correlating logs, alerts, and events from different sources.
Automate security monitoring: By continuously running searches on ingested data, correlationsearches help reduce manual efforts for SOC analysts.
Generate notable events: When a correlation search identifies a security risk, it creates a notable event in Splunk ES for investigation.
Trigger security automation: In combination with Splunk SOAR, correlation searches can initiate automated response actions, such as isolating endpoints or blocking malicious IPs.
Since correlation searches analyze relationships and patterns across multiple data sources to detect security threats, the correct answer is B. To identify patterns and relationships between multiple data sources.
References:
Splunk ES Correlation Searches Overview
Best Practices for Correlation Searches
Splunk ES Use Cases and Notable Events
NEW QUESTION # 76
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: C
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 # 77
What methods can improve dashboard usability for security program analytics?(Choosethree)
Answer: C,D,E
Explanation:
Methods to Improve Dashboard Usability in Security Analytics
A well-designed Splunk security dashboard helps SOC teams quickly identify, analyze, and respond to security threats.
#1. Using Drill-Down Options for Detailed Views (A)
Allows analysts to click on high-level metrics and drill down into event details.
Helps teams pivot from summary statistics to specific security logs.
Example:
Clicking on a failed login trend chart reveals specific failed login attempts per user.
#2. Standardizing Color Coding for Alerts (B)
Consistent color usage enhances readability and priority identification.
Example:
Red # Critical incidents
Yellow # Medium-risk alerts
Green # Resolved issues
#3. Adding Context-Sensitive Filters (D)
Filters allow users to focus on specific security events without running new searches.
Example:
A dropdown filter for "Event Severity" lets analysts view only high-risk events.
#Incorrect Answers:
C: Limiting the number of panels on the dashboard # Dashboards should be optimized, not restricted.
E: Avoiding performance optimization # Performance tuning is essential for responsive dashboards.
#Additional Resources:
Splunk Dashboard Design Best Practices
Optimizing Security Dashboards in Splunk
NEW QUESTION # 78
What are the benefits of maintaining a detection lifecycle?(Choosetwo)
Answer: A,B
Explanation:
Why Maintain a Detection Lifecycle?
Adetection lifecycleensures that security alerts, correlation searches, and automation playbooks arecontinuously refinedto maintainaccuracy, efficiency, and relevanceagainst modern threats.
#1. Detecting and Eliminating Outdated Searches (Answer A)#Removes unnecessary or redundant correlation searchesthat may slow down performance.#Prevents false positivescaused by outdated detection logic.
#Example:A Splunk ES search for anold malware variantmay no longer be effective # it should be updated to detectnew techniques used by attackers.
#2. Ensuring Detections Remain Relevant to Evolving Threats (Answer C)#Regular updatesensure thatnew MITRE ATT&CK techniquesand threat indicators are included.#Example:If attackers start usingLiving-off- the-Land (LotL) techniques, security teams mustupdate detection rules to identify suspicious PowerShell activity.
Why Not the Other Options?
#B. Scaling the Splunk deployment effectively- Lifecycle management improvesdetection accuracy, notinfrastructure scalability.#D. Automating the deployment of new detection logic- Automation helps, but lifecycle management isabout reviewing and updating detections, not just deployment.
References & Learning Resources
#Detection Management in Splunk ES: https://docs.splunk.com/Documentation/ES#Updating Threat Detections Using MITRE ATT&CK in Splunk: https://attack.mitre.org/resources#Best Practices for SOC Detection Engineering: https://splunkbase.splunk.com
NEW QUESTION # 79
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