Splunk SPLK-5001 Practice Test Questions and Exam Dumps Part17 Q321-340

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Question 321. What does an event-based detection analyze?

  1. Finding groups only
  2. Raw security events
  3. Dashboard layouts
  4. User permissions only

Correct Answer: 2. Raw security events

Explanation:

An event-based detection searches raw or normalized security events for patterns that might indicate suspicious activity. Its data can come from security domains such as access, identity, endpoint, or network sources. When its conditions are met, the detection can generate findings or intermediate findings and can also perform configured response actions. This differs from a finding-based detection, which analyzes existing findings instead of starting directly with raw security events. Splunk Enterprise Security uses event-based detections as a core method for transforming telemetry into security observations that analysts or additional analytics can investigate.

Question 322. What does a finding-based detection analyze?

  1. Raw packets only
  2. Dashboard XML
  3. Index configuration
  4. Existing findings

Correct Answer: 4. Existing findings

Explanation:

A finding-based detection analyzes existing findings and intermediate findings rather than starting directly with raw security events. It can aggregate related security observations by entity or other grouping criteria and identify patterns that represent a higher-confidence security risk. This helps reduce alert noise because several lower-level observations can be evaluated together before analysts are asked to investigate them. Splunk Enterprise Security describes finding-based detections as analytics that review findings from the risk and notable indexes and create finding groups representing potential security threats.

Question 323. What is an intermediate finding?

  1. An observation that may need further correlation
  2. A confirmed breach
  3. An index configuration
  4. A dashboard panel

Correct Answer: 1. An observation that may need further correlation

Explanation:

An intermediate finding is a security observation that indicates unusual or potentially risky behavior but might not be strong enough to represent a standalone incident. Intermediate findings can contain an entity, risk score, timestamp, threat objects, and other metadata. They are valuable because finding-based detections can correlate several intermediate findings and findings to identify a stronger security pattern. Unlike ordinary findings, intermediate findings are not displayed directly in the analyst queue for routine triage. Splunk uses them to support higher-fidelity risk-based analysis while avoiding unnecessary analyst alert volume.

Question 324. Where are findings commonly triaged?

  1. Index Manager
  2. Data Inputs
  3. Analyst queue
  4. Field Extractor

Correct Answer: 3. Analyst queue

Explanation:

Findings are displayed in the analyst queue in Mission Control so security analysts can review and triage them. From the queue, analysts can examine security context, assign findings, change status, modify urgency, update disposition, and add notes. This provides a structured operational workflow instead of requiring analysts to manually inspect every detection result through raw searches. Intermediate findings normally do not appear in the analyst queue because they are intended primarily as supporting observations for additional correlation. The queue therefore focuses analyst attention on security findings and investigations that warrant direct review.

Question 325. What replaced the term notable event in ES 8.x?

  1. Risk modifier
  2. Investigation
  3. Intermediate finding
  4. Finding

Correct Answer: 4. Finding

Explanation:

In Splunk Enterprise Security 8.0 and later, the term finding replaces the older term notable event. Findings combine important information about what a detection observed and which entity was affected. They can contain metadata such as tactics, techniques, confidence, impact, calculated risk, and threat objects. Understanding this terminology is important because older documentation or deployments might still refer to notable events, while current Enterprise Security workflows increasingly use findings. Splunk also changed the older term risk event to intermediate finding in the Enterprise Security 8.x terminology.

Question 326. What replaced the term risk event in ES 8.x?

  1. Finding group
  2. Intermediate finding
  3. Investigation
  4. Adaptive action

Correct Answer: 2. Intermediate finding

Explanation:

Splunk Enterprise Security 8.x uses the term intermediate finding for what earlier versions commonly called a risk event. Intermediate findings record potentially suspicious observations and can contain risk scores, entity information, timestamps, and threat metadata. They are typically used as input to higher-level analytics rather than being individually triaged by analysts. This terminology reflects Splunk’s newer finding-based workflow, where multiple lower-level observations can be aggregated to create stronger security findings or finding groups. Analysts working across older and newer Enterprise Security versions should recognize both terms to correctly interpret searches and documentation.

Question 327. What can a detection adjust?

  1. License capacity
  2. Dashboard theme
  3. Risk score
  4. Index bucket size

Correct Answer: 3. Risk score

Explanation:

A detection can be configured to adjust risk associated with an entity when suspicious behavior is observed. Splunk Enterprise Security detections can create findings, create intermediate findings, adjust risk scores, or perform adaptive response actions depending on the configuration. Risk scoring helps analysts evaluate several security observations together instead of treating every event as equally important. For example, different suspicious activities involving the same user can contribute to a higher overall risk picture. This risk-based approach helps prioritize entities that show repeated or more significant suspicious behavior.

Question 328. What is a finding group?

  1. Related findings combined together
  2. A CIM data model
  3. A threat feed
  4. A search macro

Correct Answer: 1. Related findings combined together

Explanation:

A finding group is a collection of related findings and intermediate findings created through finding-based detection logic. By grouping related observations, Splunk can present a stronger security story instead of forcing analysts to review many isolated alerts independently. Finding groups can be triaged by the SOC and can also be manually added to investigations. Splunk stores finding groups in KV Store collections. Grouping is particularly useful when several security observations affecting the same entity collectively indicate greater risk than any single observation would suggest on its own.

Question 329. Where are finding groups stored?

  1. Raw event buckets only
  2. Browser cache
  3. Dashboard XML
  4. KV Store collections

Correct Answer: 4. KV Store collections

Explanation:

Splunk Enterprise Security stores finding groups in KV Store collections. Finding groups are produced when finding-based detections correlate relevant findings and intermediate findings according to entity or other grouping conditions. Storing the resulting group in a structured collection allows Enterprise Security to track and present the correlated security story for analyst review. Finding groups can then be triaged or added to investigations. They should not be confused with raw security events, which remain in indexes and provide the underlying telemetry from which detections may generate findings.

Question 330. What is an analytic story?

  1. A collection of related security content
  2. A user role
  3. A raw index
  4. A lookup definition

Correct Answer: 1. A collection of related security content

Explanation:

An analytic story groups related security content around a particular threat, attack pattern, use case, or security objective. Splunk Enterprise Security provides a broad library of detections organized into analytic stories so teams can identify relevant detection content without treating every analytic as an unrelated item. An analytic story may help defenders understand a particular threat scenario and select detections that collectively provide coverage for it. Security Content Updates continue to add and update analytic stories and related detections as threats and defensive requirements change.

Question 331. What is a main goal of finding-based detection?

  1. Increase raw log volume
  2. Reduce alert noise through correlation
  3. Disable entity tracking
  4. Remove risk metadata

Correct Answer: 2. Reduce alert noise through correlation

Explanation:

Finding-based detections help reduce alert noise by correlating multiple findings and intermediate findings before presenting a stronger security result to analysts. Instead of requiring the SOC to manually triage every low-level observation, the detection can aggregate related activity at the entity level or through other criteria. Recent Splunk Security Content updates specifically highlight finding-based detections as a way to handle high volumes of related observations and help analysts focus on users or hosts that are more likely to represent meaningful threats.

Question 332. What can a finding contain?

  1. Only an event count
  2. Only a username
  3. Entity and security metadata
  4. Only dashboard settings

Correct Answer: 3. Entity and security metadata

Explanation:

A finding can contain information such as timestamp, key-value fields, entity information, summary details, MITRE ATT&CK metadata, confidence, impact, calculated risk, and threat objects. This information gives analysts more context than a simple alert message. Because the finding includes details about both the observed behavior and the affected entity, analysts can more quickly understand why the detection triggered and how important the activity might be. Splunk Enterprise Security uses these metadata-rich findings throughout Mission Control and investigation workflows.

Question 333. Which detection directly evaluates raw events?

  1. Event-based detection
  2. Finding-based detection
  3. Finding group
  4. Response plan

Correct Answer: 1. Event-based detection

Explanation:

An event-based detection evaluates raw or normalized event data directly and looks for defined patterns that might indicate a threat or anomaly. When the conditions are satisfied, it can create findings or intermediate findings depending on configuration. Finding-based detections operate one level later by analyzing findings that already exist. This distinction is important when designing detection pipelines: event-based analytics convert telemetry into observations, while finding-based analytics can correlate those observations into higher-confidence security stories.

Question 334. Which item is NOT normally triaged directly?

  1. Investigation
  2. Finding
  3. Finding group
  4. Intermediate finding

Correct Answer: 4. Intermediate finding

Explanation:

Intermediate findings are not normally displayed in the analyst queue and are therefore not directly triaged by analysts. They represent lower-level observations that may be useful when combined with other evidence. Finding-based detections can use intermediate findings together with findings to identify higher-confidence threats. Findings and investigations, by contrast, are part of the analyst-facing workflow in Mission Control. This separation is intended to reduce SOC noise by keeping weaker observations available for correlation without requiring individual manual review.

Question 335. What does a UEBA detection generate?

  1. Dashboard panels
  2. Intermediate findings
  3. New user accounts
  4. Index buckets

Correct Answer: 2. Intermediate findings

Explanation:

UEBA detections compare current user or asset behavior with learned historical baselines and generate intermediate findings when activity deviates significantly from expected behavior. These observations contribute to the entity risk score and can become part of broader risk-based analysis. Because a single anomaly does not always represent a confirmed incident, intermediate findings are appropriate for capturing the observation without immediately forcing direct analyst triage. Splunk notes that UEBA detections use statistical models and machine learning rather than relying only on fixed rules.

Question 336. What does UEBA use to detect anomalies?

  1. Static passwords
  2. Manual tags only
  3. Learned historical baselines
  4. Dashboard colors

Correct Answer: 3. Learned historical baselines

Explanation:

UEBA detections establish normal patterns for users or assets using historical behavior and then look for significant deviations from those learned baselines. This can reveal activity that fixed thresholds might miss because what is unusual for one user might be normal for another. Examples can include abnormal access times, uncommon resource use, or unusual activity volumes. Splunk Enterprise Security describes UEBA as using statistical models and machine learning to determine normal behavior and produce intermediate findings when meaningful deviations occur.

Question 337. Can UEBA detection SPL be modified directly?

  1. Always
  2. Only by analysts
  3. Only in Mission Control
  4. No

Correct Answer: 2. No

Explanation:

Splunk documentation states that administrators can tune findings produced by UEBA detections using finding exclusions, but they cannot modify the underlying SPL or detection logic directly. This differs from many ordinary event-based detections that can be customized more extensively. The controlled UEBA logic helps preserve the statistical and machine-learning behavior on which the detections depend. Analysts can still manage noise by using supported exclusion mechanisms when known legitimate behavior repeatedly generates unnecessary intermediate findings.

Question 338. What can analysts change on a finding?

  1. Status and disposition
  2. Indexed raw data
  3. Original timestamp source
  4. Sourcetype parsing rules

Correct Answer: 1. Status and disposition

Explanation:

Analysts can manage findings through the Mission Control analyst queue by changing properties such as ownership, status, urgency, and disposition and by adding investigation notes. These workflow fields help teams coordinate triage and document what happened during an investigation. Changing a finding’s workflow metadata does not rewrite the underlying source logs or modify how the original events were indexed. Splunk uses these analyst-facing fields to support collaborative SOC operations and track remediation from initial review through resolution.

Question 339. What is Detection Studio used to examine?

  1. License usage only
  2. User passwords
  3. Index buckets
  4. Detection content and coverage

Correct Answer: 4. Detection content and coverage

Explanation:

Detection Studio helps security teams work with and evaluate detection content. Splunk’s recent Security Content updates are increasingly aligned with Detection Studio as the supported direction for building and managing security analytics. Detection content can also be reviewed in the context of analytic stories and security frameworks, helping teams understand where coverage exists and where gaps may remain. Splunk’s 2026 Security Content Update notes the transition of future detection-development investment toward Detection Studio.

Question 340. What BEST improves high-volume alert handling?

  1. Show every observation separately
  2. Ignore intermediate findings
  3. Correlate related findings by entity
  4. Remove detection metadata

Correct Answer: 3. Correlate related findings by entity

Explanation:

Correlating related findings and intermediate findings by entity helps convert large volumes of lower-level observations into higher-confidence security stories. Finding-based detections are designed for this purpose and can group activity involving the same user, host, or other entity. This reduces analyst noise while preserving the evidence required to understand the threat. Recent Splunk security content emphasizes finding-based detections for automatically correlating large volumes of observations and helping analysts focus on entities that are most relevant to investigation.