Free Practice Questions for Splunk SPLK-5001 Exam

A briefing delivered by a Cyber Threat Intelligence (CTI) team to a Chief Information Security Officer (CISO) detailing the overall threat landscape is an example ofStrategicThreat Intelligence. Strategic intelligence focuses on high-level analysis of broader trends, threat actors, and potential risks to the organization over time. It is designed to inform senior leadership and influence long-term security strategies and policies. This contrasts withTacticalintelligence, which deals with immediate threats and actionable information, andOperationalintelligence, which is more focused on the details of specific threat actors or campaigns.

Splunk Enterprise Security provides a feature calledFramework Mappingthat allows correlation searches to be mapped to specific cybersecurity frameworks, including NIST 800-171, which is crucial for DoD contractors. This mapping provides context to the analyst by showing how particular searches align with compliance requirements, aiding in continuous monitoring and reassessment as mandated by the DoD. This feature is integral for organizations that need to demonstrate compliance with NIST guidelines and other security frameworks.

TheAsset and Identityframework within Splunk Enterprise Security (ES) is designed to add enriched context and correlation to the raw data fields by mapping logs to known assets (such as devices, servers, endpoints) and identities (users and accounts). This framework enhances the meaning of raw event data by associating events with relevant organizational entities, which helps in prioritization, detection, and investigation workflows.

TheAsset and Identityframework automatically tags and correlates data points with asset categories and user identities, improving detection fidelity and enabling targeted risk scoring.

Adaptive Responseis a mechanism for triggering automated actions, not a contextual framework.

Threat Intelligenceframework integrates external intelligence data but does not inherently add context to raw data fields.

Riskframework calculates risk scores based on multiple factors but builds upon context enriched by Asset and Identity.

TheSplunk Enterprise Security User Guidestates that the Asset and Identity framework is critical for making raw event data actionable through contextual enrichment and is foundational to the ES correlation searches and dashboards.

In this scenario, the analyst cannot conclude whether the Notable Event is a true positive or a false positive due to the absence of necessary logs and artifacts. The appropriate event disposition in this case is "Other," as it indicates that further action is required, such as ingesting the missing logs. The involvement of a security engineer to ensure the necessary data is available for proper investigation is implied, making "Other" the most suitable option.

Therexcommand in Splunk can be used to extract or replace data using regular expressions. To dynamically replace values with a specific pattern, such as replacing credit card numbers with "X", the mode needs to be set tosed. Thesedmode allows for string replacement within a field using regular expressions, enabling the substitution of matching patterns with a specified string.

AnIntrusion Prevention System (IPS)is a network security tool designed to continuously monitor network traffic and actively block or prevent malicious activity in real time. Unlike an Intrusion Detection System (IDS), which only alerts on suspicious activity, an IPS is inline and can take automated preventive actions such as dropping malicious packets or blocking traffic from offending IPs.

Intrusion Detection System (IDS)only detects and alerts but does not block traffic.

Packet Sniffercaptures and analyzes network packets for monitoring but lacks automated response capabilities.

SIEM (Security Information and Event Management)aggregates logs and alerts but does not directly block traffic.

TheSplunk Cybersecurity Defense Analyst Study Guideexplains that IPS devices are critical in defense-in-depth strategies to prevent intrusions before they cause damage.

The main difference between hypothesis-driven and data-driven threat hunting lies in the approach. Inhypothesis-drivenhunting, the hunter starts with a theory or hypothesis about what kind of malicious activity might be occurring and then searches the data to confirm or refute that hypothesis. On the other hand,data-drivenhunting involves sifting through existing datasets to uncover patterns, anomalies, or activities that were not initially suspected. Hypothesis-driven approaches are more focused and often guided by threat intelligence or knowledge of attacker behaviors, while data-driven approaches rely on broad data analysis to identify unexpected threats.

Splunk Answersis a community-driven Q&A platform where users can ask questions and share knowledge about Splunk. It is known for providing community-sourced answers to a wide range of questions, including SPL (Search Processing Language) queries, configuration issues, and general best practices. Users can contribute by answering questions based on their own experiences, making it a valuable resource for troubleshooting and learning.

B. Splunk Lantern:This is a resource for best practices, how-tos, and use case guides, but it’s not a community-sourced Q&A platform.

C. Splunk Guidebook:This is not a known resource in the context of community-sourced answers.

D. Splunk Documentation:While highly detailed and official, it is not community-sourced but rather maintained by Splunk's own teams.

In Splunk,streaming commandsprocess each event individually as it is passed through the search pipeline and should be placed beforeaggregating commands, which operate on the entire set of results at once. This best practice ensures efficient processing and minimizes resource usage, as streaming commands reduce the amount of data before aggregation occurs. This approach leads to faster and more efficient searches. In contrast, the other options, such as using wildcards excessively or searching over all time, can lead to performance issues and excessive data processing.