Splunk Certified Cybersecurity Defense Engineer SPLK-5002 Exam Practice Test

Answer : B

How to Reduce False Positives in Correlation Searches?

High false positives can overwhelm SOC teams, causing alert fatigue and missed real threats. The best solution is to fine-tune suppression rules and refine thresholds.

How Suppression Rules & Threshold Tuning Help: Suppression Rules: Prevent repeated false positives from low-risk recurring events (e.g., normal system scans). Threshold Refinement: Adjust sensitivity to focus on true threats (e.g., changing a login failure alert from 3 to 10 failed attempts).

Example in Splunk ES: Scenario: A correlation search generates too many alerts for failed logins. Fix: SOC analysts refine detection thresholds:

Suppress alerts if failed logins occur within a short timeframe but are followed by a successful login.

Only trigger an alert if failed logins exceed 10 attempts within 5 minutes.

Why Not the Other Options?

A. Increase the frequency of the correlation search -- Increases search load without reducing false positives. C. Disable the correlation search temporarily -- Leads to blind spots in detection. D. Limit the search to a single index -- May exclude critical security logs from detection.

Reference & Learning Resources

Splunk ES Correlation Search Optimization Guide: https://docs.splunk.com/Documentation/ES Reducing False Positives in SOC Workflows: https://splunkbase.splunk.com Fine-Tuning Security Alerts in Splunk: https://www.splunk.com/en_us/blog/security

Answer : C

If a user queries an index during a high-priority incident but sees incomplete results, it is likely that the indexers are overloaded, causing queue bottlenecks.

Why Indexer Queue Capacity Issues Cause Incomplete Results:

When indexing queues fill up, incoming data cannot be processed efficiently.

Search results may be incomplete or delayed if events are still in the indexing queue and not fully written to disk.

Heavy search loads during incidents can also increase pressure on indexers.

How to Fix It:

Monitor indexing queues via the Monitoring Console (indexing>indexing performance).

Check metrics.log on indexers for max_queue_size_exceeded warnings.

Increase indexer capacity or optimize search scheduling to reduce load.

Incorrect Answers: A. Buckets in the warm state are inaccessible -- Warm buckets are still searchable unless there is a storage failure. B. Data normalization was not applied -- Normalization affects data consistency but does not cause incomplete results. D. The search head configuration is outdated -- This does not affect indexing, only the execution of searches.

Answer : B

Security teams use Splunk Enterprise Security (ES) and Splunk SOAR to integrate with firewalls, endpoint security, and SIEM tools for automated threat response.

Workflow Actions (B) - Key Integration Feature

Allows analysts to trigger automated actions directly from Splunk searches and dashboards.

Can integrate with SOAR playbooks, ticketing systems (e.g., ServiceNow), or firewalls to take action.

Example:

Block an IP on a firewall from a Splunk dashboard.

Trigger a SOAR playbook for automated threat containment.

Incorrect Answers:

A . Data Model Acceleration Speeds up searches, but doesn't handle integrations.

C . Summary Indexing Stores summarized data for reporting, not automation.

D . Event Sampling Reduces search load, but doesn't trigger automated actions.

Additional Resources:

Splunk Workflow Actions Documentation

Automating Response with Splunk SOAR

Answer : A

If there is a delay in data being indexed from a remote location, even though the Universal Forwarder (UF) is correctly configured, the issue is likely a queue blockage or network latency.

Steps to Diagnose and Fix Forwarder Delays:

Check Forwarder Logs (splunkd.log) for Queue Issues (A)

Look for messages like TcpOutAutoLoadBalanced or Queue is full.

If queues are full, events are stuck at the forwarder and not reaching the indexer.

Monitor Forwarder Health Using metrics.log

Use index=_internal source=*metrics.log* group=queue to check queue performance.

Incorrect Answers: B. Increase the indexer memory allocation -- Memory allocation does not resolve forwarder delays. C. Optimize search head clustering -- Search heads manage search performance, not forwarder ingestion. D. Reconfigure the props.conf file -- props.conf affects event processing, not ingestion speed.

Splunk Forwarder Troubleshooting Guide

Monitoring Forwarder Queue Performance

Answer : B

Splunk SOAR (Security Orchestration, Automation, and Response) playbooks help SOC teams automate, orchestrate, and respond to threats faster.

Key Benefits of SOAR Playbooks

Automates Repetitive Tasks

Reduces manual workload for SOC analysts.

Automates tasks like enriching alerts, blocking IPs, and generating reports.

Orchestrates Multiple Security Tools

Integrates with firewalls, EDR, SIEMs, threat intelligence feeds.

Example: A playbook can automatically enrich an IP address by querying VirusTotal, Splunk, and SIEM logs.

Accelerates Incident Response

Reduces Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR).

Example: A playbook can automatically quarantine compromised endpoints in CrowdStrike after an alert.

Incorrect Answers:

A . Manually running searches across multiple indexes SOAR playbooks are about automation, not manual searches.

C . Improving dashboard visualization capabilities Dashboards are part of SIEM (Splunk ES), not SOAR playbooks.

D . Enhancing data retention policies Retention is a Splunk Indexing feature, not SOAR-related.

Additional Resources:

Splunk SOAR Playbook Guide

Automating Threat Response with SOAR

Answer : A

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.

Reference & 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

Answer : C

Why Use Index-Time Transformations for One-Time Parsing & Indexing?

Splunk parses and indexes data once during ingestion to ensure efficient storage and search performance. Index-time transformations ensure that logs are:

Parsed, transformed, and stored efficiently before indexing. Normalized before indexing, so the SOC team doesn't need to clean up fields later. Processed once, ensuring optimal storage utilization.

Example of Index-Time Transformation in Splunk: Scenario: The SOC team needs to mask sensitive data in security logs before storing them in Splunk. Solution: Use an INDEXED_EXTRACTIONS rule to:

Redact confidential fields (e.g., obfuscate Social Security Numbers in logs).

Rename fields for consistency before indexing.