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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building Effective Security Processes and Programs | 20% | - Documentation and standard operating procedures development - Threat intelligence research, integration and development - Risk and detection prioritization methodologies |
| Topic 2: Auditing and Reporting on Security Programs | 10% | - Security report creation and population - Dashboard building for program analytics - Security metrics development and optimization |
| Topic 3: Data Engineering | 10% | - Data review and analysis - Data normalization methods and application - Performant data indexing creation and maintenance |
| Topic 4: Automation and Efficiency | 20% | - Integration and automation capability comparison between Enterprise Security and SOAR - Response automation using SOAR playbooks - Automation and orchestration for standard operating procedures - Case management optimization - REST API usage and description |
| Topic 5: Detection Engineering | 40% | - Generating effective Notable Events and findings - Incorporating context into detections - Creation and tuning of detections and correlation searches - Detection lifecycle management - Risk-based modifiers and detections |
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NEW QUESTION # 82
Which field in the risk index is used to describe the activity within a finding?
Answer: C
Explanation:
The correct field is risk_message . In Splunk Enterprise Security Risk-Based Alerting, risk_message provides a human-readable description of the suspicious activity represented by a risk event. It gives analysts contextual information explaining what happened and why the risk contribution was generated.
This should be distinguished from risk_object , which identifies the entity receiving risk-for example, a username, host, system, or other security-relevant object. A typical risk event therefore combines fields conceptually such as:
risk_object= " jsmith "
risk_object_type= " user "
risk_score=40
risk_message= " User executed suspicious PowerShell command "
The risk object answers who or what is accumulating risk , while risk_message explains the activity responsible for that risk . risk_description and risk_reason are distractors and are not the standard field requested.
The uploaded guide strongly covers Risk Framework concepts, including risk objects, risk scores, Risk Factors, and Risk Analysis, although this exact field-name question is not presented verbatim in the supplied
60-question set.
Study Guide topics: Risk Framework, risk index, risk_message, risk objects, Risk-Based Alerting, contextual findings.
NEW QUESTION # 83
Which of the following is a reason to utilize an index-based search (index=...) over a data model search (| tstats...) in a detection?
Answer: A
Explanation:
An index-based search should be used when the raw event fields contain more detail than the data model. Data models normalize and may omit certain fields, so searching the index directly ensures all relevant information is available for the detection.
NEW QUESTION # 84
When developing security metrics, why would a Key Performance Indicator (KPI) that focuses on total perimeter firewall blocks be an ineffective metric?
Answer: C
Explanation:
A total count of blocked firewall connections describes an outcome generated by the control , rather than measuring how effectively the firewall itself performs against an established operational objective. It is therefore better characterized as a Key Result Indicator (KRI) in the terminology used by the course material.
For example, observing five million blocked connections does not demonstrate that a firewall is performing better than one that blocks one million. The total is heavily influenced by external conditions such as Internet scanning, bot activity, exposure of public services, and changing adversary traffic. The number can increase even when no improvement has occurred in firewall configuration, reliability, policy quality, or security effectiveness.
A meaningful KPI should connect directly to measurable performance-for example control availability, policy deployment accuracy, remediation time, rule-review compliance, or another defined operational objective. Firewall-block volume may remain useful as contextual or trend information, but treating it as a performance metric can produce misleading conclusions about security-program effectiveness.
The supplied study material contains this firewall KPI/KRI distinction.
Study Guide topics: security metrics, KPI versus KRI, control effectiveness, perimeter security, security- program reporting.
NEW QUESTION # 85
What are the essential components of risk-based detections in Splunk?
Answer: A
Explanation:
What Are Risk-Based Detections in Splunk?
Risk-based detections in Splunk Enterprise Security (ES) assign risk scores to security events based on threat severity and asset criticality.
#Key Components of Risk-Based Detections:1##Risk Modifiers - Adjusts risk scores based on event type (e.
g., failed logins, malware detections).2##Risk Objects - Entities associated with security events (e.g., users, IPs, devices).3##Risk Scores - Numerical values indicating the severity of a risk.
#Example in Splunk Enterprise Security:#Scenario: A high-privilege account (Admin) fails multiple logins from an unusual location.#Splunk ES applies risk-based detection:
Failed logins add +10 risk points
Login from a suspicious country adds +15 points
Total risk score exceeds 25 # Triggers an alert
Why Not the Other Options?
#B. Summary indexing, tags, and event types - Summary indexing stores precomputed data, but doesn't drive risk-based detection.#C. Alerts, notifications, and priority levels - Important, but risk-based detection is based on scoring, not just alerts.#D. Source types, correlation searches, and asset groups - Helps in data organization, but not specific to risk-based detections.
References & Learning Resources
#Splunk ES Risk-Based Alerting Guide: https://docs.splunk.com/Documentation/ES#Risk-Based Detections
& Scoring in Splunk: https://www.splunk.com/en_us/blog/security/risk-based-alerting.html#Best Practices for Risk Scoring in SOC Operations: https://splunkbase.splunk.com
NEW QUESTION # 86
When creating a detection that searches user activity across CIM-compliant data, which CIM field should be reviewed to ensure that data is aggregated appropriately?
Answer: C
Explanation:
The user field is the normalized CIM field for user activity across data sources. Reviewing and using this field ensures that data from different sources is properly aggregated, enabling consistent detection logic across CIM-compliant datasets.
NEW QUESTION # 87
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