Splunk SPLK-5001 Dumps in PDF and Online - Page: 1

QUESTION: 1

Which Enterprise Security framework provides a mechanism for running preconfigured actions within the Splunk platform or integrating with external applications?

Asset and Identity
Notable Event
Threat Intelligence
Adaptive Response

Answer(s): D

Explanation:

Reference:

https://dev.splunk.com/enterprise/docs/devtools/enterprisesecurity/

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Which of the following Splunk Enterprise Security features allows industry frameworks such as CIS Critical Security Controls, MITRE ATT&CK, and the Lockheed Martin Cyber Kill Chain® to be mapped to Correlation Search results?

Annotations
Playbooks
Comments
Enrichments

Answer(s): A

Explanation:

Reference:

https://docs.splunk.com/Documentation/ES/7.3.2/Admin/Correlationsearchoverview

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QUESTION: 3

Which of the following is the primary benefit of using the CIM in Splunk?

It allows for easier correlation of data from different sources.
It improves the performance of search queries on raw data.
It enables the use of advanced machine learning algorithms.
It automatically detects and blocks cyber threats.

Answer(s): A

Explanation:

Reference:

https://docs.splunk.com/Documentation/CIM/5.3.2/User/Overview

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QUESTION: 4

Tactics, Techniques, and Procedures (TTPs) are methods or behaviors utilized by attackers. In which framework are these categorized?

NIST 800-53
ISO 27000
CIS18
MITRE ATT&CK

Answer(s): D

Explanation:

Reference:

https://cymulate.com/cybersecurity-glossary/tactics-techniques-procedures/

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QUESTION: 5

A threat hunter executed a hunt based on the following hypothesis:
As an actor, I want to plant rundll32 for proxy execution of malicious code and leverage Cobalt Strike for Command and Control.
Relevant logs and artifacts such as Sysmon, netflow, IDS alerts, and EDR logs were searched, and the hunter is confident in the conclusion that Cobalt Strike is not present in the company’s environment.
Which of the following best describes the outcome of this threat hunt?

The threat hunt was successful because the hypothesis was not proven.
The threat hunt failed because the hypothesis was not proven.
The threat hunt failed because no malicious activity was identified.
The threat hunt was successful in providing strong evidence that the tactic and tool is not present in the environment.

Answer(s): D

Explanation:

Reference:

https://www.cybereason.com/blog/how-to-generate-a-hypothesis-for-a-threat-hunt-techniques

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QUESTION: 6

A Risk Notable Event has been triggered in Splunk Enterprise Security, an analyst investigates the alert, and determines it is a false positive.
What metric would be used to define the time between alert creation and close of the event?

MTTR (Mean Time to Respond)
MTBF (Mean Time Between Failures)
MTTA (Mean Time to Acknowledge)
MTTD (Mean Time to Detect)

Answer(s): A

Explanation:

Reference:

https://docs.splunk.com/Documentation/ES/7.3.2/User/Triagenotableevents

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QUESTION: 7

Which SPL syntax would be used to perform statistical queries on indexed fields to calculate the cumulative total risk by the system or user in the most efficient way?

| from datamodel:"Risk"."All Risk" | table risk_score risk_object
index=risk |stats sum(risk_score) as risk_score count by risk_object
index=* |stats sum(risk_score) as risk_score count by risk_object
| tstats ‘summariesonly’ sum(All_Risk.calculated_risk_score) as risk_score from datamodel=Risk.All_Risk by All_Risk.risk_object

Answer(s): D

Explanation:

Using tstats with the summariesonly flag against the Risk data model leverages Splunk’s accelerated data model summaries to compute the cumulative risk score by object entirely from tsidx summaries, making it far more efficient than raw-event searches.

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QUESTION: 8

Which of the following is a reason to use Data Model Acceleration in Splunk?

To quickly model various responses to a particular vulnerability.
To retrieve data faster than from a raw index.
To normalize the data associated with threats.
To rapidly compare the use of various algorithms to detect anomalies.

Answer(s): B

Explanation:

Data Model Acceleration builds and maintains summary indexes (tsidx summaries) for your data models, allowing tstats and other accelerated searches to pull results directly from these summaries instead of scanning the full raw events - dramatically speeding up query performance.

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Splunk Certified Cybersecurity Defense Analyst SPLK-5001 Dumps in PDF

Free Splunk SPLK-5001 Real Questions (page: 1)

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