SPLK-5002 Splunk Certified Cybersecurity Defense Engineer Questions and Answers

Threat intelligence in Splunk Enterprise Security (ES) enhances SOC capabilities by identifying known attack patterns, suspicious activity, and malicious indicators.

Essential Steps in Developing Threat Intelligence:

Collecting Data from Trusted Sources (A)

Gather data from threat intelligence feeds (e.g., STIX, TAXII, OpenCTI, VirusTotal, AbuseIPDB).

Include internal logs, honeypots, and third-party security vendors.

Analyzing and Correlating Threat Data (C)

Use correlation searches to match known threat indicators against live data.

Identify patterns in network traffic, logs, and endpoint activity.

Operationalizing Intelligence Through Workflows (E)

Automate responses using Splunk SOAR (Security Orchestration, Automation, and Response).

Enhance alert prioritization by integrating intelligence into risk-based alerting (RBA).

Splunk prevents duplicate data from being indexed through event parsing, which occurs during the data ingestion process.

How Event Parsing Prevents Duplicate Data:

Splunk’s indexer parses incoming data and assigns unique timestamps, metadata, and event IDs to prevent reindexing duplicate logs.

CRC Checks (Cyclic Redundancy Checks) are applied to avoid duplicate event ingestion.

Index-time filtering and transformation rules help detect and drop repeated data before indexing.

In Splunk Enterprise Security (ES), notable events are generated by correlation searches, which are predefined searches designed to detect security incidents by analyzing logs and alerts from multiple data sources. Adding additional context to these notable events enhances their value for analysts and improves the efficiency of incident response.

To incorporate additional context, you can:

Use lookup tables to enrich data with information such as asset details, threat intelligence, and user identity.

Leverage KV Store or external enrichment sources like CMDB (Configuration Management Database) and identity management solutions.

Apply Splunk macros orevalcommands to transform and enhance event data dynamically.

Use Adaptive Response Actions in Splunk ES to pull additional information into a notable event.

The correct answer is A. By adding enriched fields during search execution, because enrichment occurs dynamically during search execution, ensuring that additional fields (such as geolocation, asset owner, and risk score) are included in the notable event.

References:

Splunk ES Documentation on Notable Event Enrichment

Correlation Search Best Practices

Using Lookups for Data Enrichment

Summary indexing in Splunk improves search efficiency by storing pre-aggregated data, reducing the need to process large datasets repeatedly.

Key Benefits of Summary Indexing:

Improves Search Performance on Aggregated Data (B)

Reduces query execution time by storing pre-calculated results.

Helps SOC teams analyze trends without running resource-intensive searches.

Increases Data Retention Period (D)

Raw logs may have short retention periods, but summary indexes can store key insights for longer.

Useful for historical trend analysis and compliance reporting.

Lean Six Sigma (LSS) is a process improvement methodology used to enhance operational efficiency by reducing waste, eliminating errors, and improving consistency.

Primary Function of Lean Six Sigma in a Security Program:

Improves security operations efficiency by optimizing alert handling, threat hunting, and incident response workflows.

Reduces unnecessary steps in SOC processes, eliminating redundancies in threat detection and response.

Enhances decision-making by using data-driven analysis to improve security metrics and Key Performance Indicators (KPIs).