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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Engineering | 10% | - Performant data indexing creation and maintenance - Data review and analysis - Data normalization methods and application |
| Topic 2: Auditing and Reporting on Security Programs | 10% | - Security metrics development and optimization - Security report creation and population - Dashboard building for program analytics |
| Topic 3: Automation and Efficiency | 20% | - Case management optimization - Automation and orchestration for standard operating procedures - REST API usage and description - Integration and automation capability comparison between Enterprise Security and SOAR - Response automation using SOAR playbooks |
| Topic 4: 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 5: Detection Engineering | 40% | - Detection lifecycle management - Risk-based modifiers and detections - Incorporating context into detections - Creation and tuning of detections and correlation searches - Generating effective Notable Events and findings |
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NEW QUESTION # 92
When building detections using the Authentication Data Model, which values are recommended for use against the actions field?
Answer: A
Explanation:
In the Authentication Data Model, the recommended values for the action field are success, failure, pending, and error. These standardized values ensure consistent mapping across authentication data sources for accurate detection and reporting.
NEW QUESTION # 93
The SOC notices over the course of an investigation there are numerous logs like the following:
14-Apr-2024 20:16:49.083 client 15.111.116.918*18345 UDP: query:
reallybad.c2.com IN A response: SERVFAIL +E
What detection should be created to alert on this behavior for the future?
Answer: B
Explanation:
The log shows repeated DNS query failures (SERVFAIL) to a suspicious domain (reallybad.c2.com). The correct detection to create is Excessive DNS Failures, which alerts on abnormal patterns of failed DNS lookups that may indicate command-and-control or malware activity.
NEW QUESTION # 94
What is a key feature of effective security reports for stakeholders?
Answer: C
Explanation:
Effective stakeholder reporting should provide high-level summaries supported by actionable insights .
Senior security, business, compliance, and operational stakeholders generally need information that communicates security posture, trends, material risks, control effectiveness, and required decisions without forcing them to interpret individual raw events.
An effective report therefore translates operational SOC data into meaningful measurements such as detection trends, response-time metrics, high-risk entities, recurring incident categories, coverage gaps, or control- performance indicators. Where detailed evidence is required, supporting event-level information can remain available through drilldowns or appendices, but it should not dominate the executive-level presentation.
Option B is unsuitable because exhaustive event logs create excessive detail and obscure the conclusions stakeholders need. Option C incorrectly assumes all stakeholders have the same technical requirements.
Option D is also incorrect because compliance-related measurements may be essential to governance, audit, and risk-management audiences.
The supplied Cybersecurity Defense Engineer material directly emphasizes meaningful security metrics and distinguishes useful performance measurements from raw activity counts, such as total firewall blocks.
Study Guide topics: security-program reporting, SOC metrics, KPIs, stakeholder communication, actionable reporting, control effectiveness.
NEW QUESTION # 95
A cybersecurity engineer notices a delay in retrieving indexed data during a security incident investigation.
The Splunk environment has multiple indexers but only one search head.
Which approach can resolve this issue?
Answer: D
Explanation:
Why Usetstatsfor Faster Searches?
When a cybersecurity engineer experiences delays in retrieving indexed data, the best way to improve search performance is to usetstatsinstead of raw searches.
#What iststats?tstatsis a high-performance command that queries data from indexed fields only, rather than scanning raw events. This makes searches significantly faster and more efficient.
#Why is This the Best Approach?
tstatssearches are 10-100x faster than raw event searches.
It leverages metadata and indexed fields, reducing search load.
It minimizes memory and CPU usage on the search head and indexers.
#Example Use Case:#Scenario: The SOC team is investigating failed logins across multiple indexers.#Using a raw search:
index=security sourcetype=auth_logs action=failed | stats count by user
#Problem: This query scans millions of raw events, causing slow performance.
#Optimized usingtstats:
| tstats count where index=security sourcetype=auth_logs action=failed by user
#Advantage: Faster results without scanning raw events.
Why Not the Other Options?
#A. Increase search head memory allocation - May help, but inefficient queries will still slow down searches.
#C. Configure a search head cluster - A single search head isn't necessarily the problem; improvingsearch performance is more effective.#D. Implement accelerated data models - Useful for prebuilt dashboards, but won't improve ad-hoc searches.
NEW QUESTION # 96
A company wants to implement risk-based detection for privileged account activities.
Whatshould they configure first?
Answer: D
Explanation:
Why Configure Asset & Identity Information for Privileged Accounts First?
Risk-based detection focuses on identifying and prioritizing threats based on the severity of their impact. For privileged accounts (admins, domain controllers, finance users), understanding who they are, what they access, and how they behave is critical.
#Key Steps for Risk-Based Detection in Splunk ES:1##Define Privileged Accounts & Groups - Identify high- risk users (Admin, HR, Finance, CISO).2##Assign Risk Scores - Apply higher scores to actions involving privileged users.3##Enable Identity & Asset Correlation - Link users to assets for better detection.
4##Monitor for Anomalies - Detect abnormal login patterns, excessive file access, or unusual privilege escalation.
#Example in Splunk ES:
A domain admin logs in from an unusual location # Trigger high-risk alert A finance director downloads sensitive payroll data at midnight # Escalate for investigation Why Not the Other Options?
#B. Correlation searches with low thresholds - May generate excessive false positives, overwhelming the SOC.#C. Event sampling for raw data - Doesn't provide context for risk-based detection.#D. Automated dashboards for all accounts - Useful for visibility, but not the first step for risk-based security.
References & Learning Resources
#Splunk ES Risk-Based Alerting (RBA): https://www.splunk.com/en_us/blog/security/risk-based-alerting.
html#Privileged Account Monitoring in Splunk: https://docs.splunk.com/Documentation/ES/latest/User
/RiskBasedAlerting#Implementing Privileged Access Security (PAM) with Splunk: https://splunkbase.splunk.
com
NEW QUESTION # 97
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