Splunk Updated SPLK-5002 Exam Questions and Answers by ivar

Triage generally provides the lowest-friction opportunity for replacing manual SOC work with automation because much of triage consists of deterministic, repetitive information-gathering and enrichment tasks.

A SOAR playbook can automatically retrieve reputation information, collect endpoint details, query identity context, check threat intelligence, detonate suspicious files or URLs, deduplicate findings, and assemble evidence before an analyst reviews the incident. These activities are generally reversible and low impact compared with active response operations. The supplied material demonstrates this principle through automation scenarios where SOAR handles repetitive Attack Analyzer submission and data-collection steps before presenting the information to an analyst.

Containment introduces greater friction because actions such as disabling an account or isolating a production endpoint can disrupt business operations. Remediation may involve deleting files, changing configurations, resetting credentials, or restoring systems and therefore generally requires stronger controls. Rendering a verdict frequently requires contextual human judgment, particularly where evidence is ambiguous.

Automating triage first therefore provides high efficiency gains while maintaining relatively low operational risk.

Study Guide topics: SOAR automation, triage, enrichment, incident-response lifecycle, automation guardrails, containment, remediation.

The appropriate analytic is Excessive DNS Failures . The decisive evidence in the example is the DNS query followed by a SERVFAIL response. SERVFAIL is a DNS response condition indicating that the DNS server was unable to complete the requested resolution successfully. Repeated occurrences therefore represent DNS-resolution failures rather than authentication, endpoint, or generic network failures.

A detection engineer could aggregate these events across an appropriate time window and evaluate dimensions such as source host, queried domain, client, or response code. The objective is to distinguish ordinary occasional resolution failures from anomalous concentrations that warrant investigation.

The example is particularly security-relevant because the queried name resembles a command-and-control domain. However, the detection name requested by the question is driven by the observable pattern in the telemetry: repeated failed DNS resolutions. Such activity can result from misconfiguration, unavailable authoritative infrastructure, transient DNS problems, or suspicious software repeatedly attempting to resolve unavailable infrastructure. Analysts would use additional context to determine the actual cause.

None of the other options corresponds directly to the DNS SERVFAIL evidence shown in the event.

Study Guide topics: DNS telemetry, SERVFAIL, threshold-based detections, network security monitoring, DNS analytics, detection operationalization.

The preferred approach is tstats , because tstats operates against indexed metadata rather than requiring Splunk to retrieve and process every matching raw event. A conceptual implementation is:

| tstats values(sourcetype) WHERE index=* BY index

This produces one result per visible index and lists the sourcetypes associated with each index. It is significantly more efficient than executing:

index=* | stats ...

because the latter can require broad raw-event retrieval across every searchable index. In a large security deployment containing billions of events, that difference is operationally significant.

The tstats command is particularly useful when the required information can be derived from indexed fields or accelerated data structures. Here, both index and sourcetype information can be obtained without inspecting full _raw event payloads.

The phrase " most efficient " is therefore central to the question. Several approaches may theoretically obtain similar information, but a broad raw-event search is unnecessarily expensive when indexed metadata already contains what is required.

This question appears on page 2 of the supplied material.

Study Guide topics: SPL efficiency, tstats, indexed metadata, index discovery, sourcetype inventory, search optimization.

The Enterprise Security threat-intelligence lookup associated with file-based intelligence is file_intel .

Splunk Enterprise Security organizes threat-intelligence indicators according to observable type. This allows the Threat Intelligence Framework to normalize and match compatible indicators against event telemetry. File-oriented intelligence can contain characteristics such as file hashes, file names, or other file-related observables used to identify known malicious artifacts.

The naming convention is important. file_hash describes a type of file indicator but is not the threat-intelligence lookup name requested by the question. user_intel and user_hash concern user-oriented naming and do not correspond to the file intelligence collection.

The supplied study material demonstrates the same Threat Intelligence Framework design by asking which intelligence KV store contains malicious FQDNs, reinforcing that ES separates intelligence into purpose-specific collections such as service_intel. The exact file_intel question is not shown verbatim in the uploaded 60-question set, but the collection naming and threat-intelligence architecture are consistent with the framework tested there.

Study Guide topics: Threat Intelligence Framework, file_intel, file indicators, IOC normalization, threat matching, KV Store intelligence collections.