Splunk SPLK-5001 Splunk Certified Cybersecurity Defense Analyst Exam Practice Test

In Splunk, when an analyst is building a search and finds that extracted fields are not appearing, it often relates to the search mode being used.Smart ModeorVerbose Modeare better suitedfor field extraction as they allow Splunk to automatically extract and display fields based on the data being searched.

Search Modes in Splunk:

Fast Mode:Optimizes search performance by limiting field extractions to only those required by the search. If the analyst is in Fast Mode, non-required fields may not be extracted or displayed.

Smart Mode:Balances performance and field extraction, allowing fields to be automatically extracted and made available for analysis.

Verbose Mode:Extracts all fields and provides the most complete view of the data, though it may be slower.

Incorrect Options:

A. The analyst does not have the proper role to search this data:If this were the case, the analyst might not be able to search at all, rather than just missing extracted fields.

B. The analyst is searching newly indexed data that was improperly parsed:This would likely lead to no data being returned, rather than just missing fields.

C. The analyst did not add the extract command to their search pipeline:Field extraction in Splunk is usually automatic unless specific commands are used; the issue here is more likely related to search mode.

Splunk Documentation:Search modes and their impact on field extraction.

References:

In the context of continuous monitoring, theImplement and Collectstage involves adding data sources, creating detections, and building drilldowns. This stage is focused on the practical setup and configuration necessary to ensure that monitoring systems are properly gathering the necessary data and that the relevant detection mechanisms are in place to identify potential threats. Other stages, such asAnalyze and Report, are more focused on the interpretation and presentation of this data after collection.

TheEnterprise Security Content Update (ESCU)app is a pre-packaged app that delivers security content and detections on a regular, ongoing basis for Splunk Enterprise Security (ES) and Splunk SOAR. ESCU provides regular updates with new correlation searches, dashboards, and other content that help organizations stay up-to-date with the latest threats and detection techniques. This app is specifically designed to enhance the capabilities of Splunk ES by providing out-of-the-box security content that can be customized and used immediately.

The log entry showing the same request repeated millions of times indicates aDenial of Service (DoS) Attack, where the server is overwhelmed by a flood of requests to a specific resource, in this case, the/login/page. This type of attack is aimed at making the server unavailable to legitimate users by exhausting its resources.

Denial of Service Attack:

A DoS attack involves a single attacker (or sometimes a small number of sources) sending a massive number of requests to a target server, overwhelming its ability to handle legitimate traffic.

The repetitive log entries reflect the server's inability to process legitimate requests due to the overwhelming number of identical requests.

Incorrect Options:

B. Distributed Denial of Service Attack:This involves multiple sources attacking simultaneously. The log provided does not indicate multiple sources, which would be characteristic of a DDoS attack.

C. Cross-Site Scripting Attack:This attack involves injecting malicious scripts into webpages viewed by other users, not overwhelming a server with traffic.

D. Database Injection Attack:This is an attack against a database via SQL injection or similar techniques, not overwhelming a server with traffic.

Web Server Security:Understanding DoS attacks is critical for securing web servers and mitigating these types of disruptions.

References:

Tacticsare the overarching objectives or strategies attackers use during their operations, whiletechniquesare the specific methods used to achieve these tactics. In this case,gathering information about a target(often referred to as Reconnaissance) is atacticbecause it represents a high-level objective of understanding the target. The other options provided (persistence, phishing, privilege escalation) are specifictechniquesused to achieve the broader goals or tactics.

Theforeachcommand in Splunk is used to iterate over a list of fields that match a wildcard expression and apply a subsearch or function to each of them. This is particularly useful when you need to perform an operation across multiple fields dynamically identified by a wildcard pattern. None of the other options (rex,makeresults, ortransaction) are designed for this specific purpose. Theforeachcommand allows for flexible and efficient processing of multiple fields without having to explicitly name them all.

The Lockheed Martin Cyber Kill Chain® is a widely recognized framework that breaks down the stages of a cyber attack. The stages are: Reconnaissance, Weaponization, Delivery, Exploitation, Installation, Command and Control (C2), and Actions on Objectives. The scenario described—modifying the registry on a compromised Windows system to ensure malware runs at boot time—fits into theInstallationphase. This phase involves placing a persistent backdoor or other malicious software on the victim's system, ensuring it can be executed again, even after a system reboot. By modifying the registry, the attacker is achieving persistence, a classic example of the Installation phase.

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.

The scenario described is an example ofLeast Frequency of Occurrence Analysis. This threat-hunting technique focuses on identifying events or behaviors that occur infrequently, under the assumption that rare activities could indicate abnormal or suspicious behavior. By filtering out users who log in frequently and focusing on those with rare login attempts, the threat hunter aims to identify potentially suspicious activity that warrants further investigation. This technique is particularly effective in detecting stealthy attacks that might evade more common detection methods.

Top of Form

Bottom of Form

TheevalSPL expression in Splunk supports several categories of functions, includingJSON functions(e.g.,spath),Text functions(e.g.,substr,trim), andComparison and Conditional functions(e.g.,if,case). However,Threat functionsis not a valid category within theevalcommand. Theevalcommand is primarily used for transforming and manipulating data in various ways, but it does not include a category specifically for threat-related functions.

Tactical intelligenceprovides insights into the specific behaviors, tools, and techniques used by threat actors. When a Cyber Threat Intelligence (CTI) team produces a report detailing a threat actor’s typical behaviors and intent, they are delivering tactical intelligence. This type of intelligence is actionable and directly supports defenders in identifying, mitigating, and responding to threats in a timely manner.

Tactical Intelligence:

Focuses on the specific, detailed activities of threat actors, such as the Tactics, Techniques, and Procedures (TTPs) they employ.

This intelligence helps in creating defensive strategies, such as refining detection rules, improving incident response plans, and enhancing threat hunting efforts.

Incorrect Options:

A. Operational:Operational intelligence involves real-time information and insights that support ongoing operations, often within a narrow timeframe.

B. Executive:Executive intelligence is high-level and strategic, intended for decision-makers and typically involves summaries rather than detailed technical information.

D. Strategic:Strategic intelligence is long-term and broad in scope, focusing on overall trends and the geopolitical context, rather than specific TTPs.

CTI Frameworks:Standards such as the MITRE ATT&CK framework, which classify tactical intelligence within the spectrum of threat intelligence.

References:

Thestatscommand is used to generate statistics, such as counts, over specific fields. In this case, the commandindex=security_logs eventtype=failed_login | stats count as failed_attempts by src_ip | sort -failed_attemptscreates a temporary table that counts the number of failed login attempts (failed_attempts) for each source IP (src_ip). Thesort -failed_attemptsensures the results are ordered by the number of failed attempts in descending order, making it easier for an analyst to identify problematic IPs.

In Splunk Enterprise Security, when assets are properly defined and enabled, the fieldsrc_categoryis automatically added to search results. This field categorizes the source IP addresses according to their asset classification, which helps in analyzing and filtering search results based on the type of assets involved in an event. Proper asset and identity management within Splunk ES enhances the ability to contextualize and prioritize security incidents.

To investigate which process initiated a network connection, an analyst would use theEndpointdata model in Splunk Enterprise Security. The Endpoint data model contains fields related to processes, file activity, and host-level data, which are essential for tracing back the source of suspicious network activity to the specific process or application that initiated it. This is crucial for understanding the scope of an attack and determining the origin of malicious network traffic.

Top of Form

Bottom of Form

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 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 rangeof 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.

Splunk Answers Platform:Splunk Answers

Incorrect Options:References:

The step-by-step description provided is an example of aTechniqueas defined in the MITRE ATT&CK framework. Techniques are the specific methods adversaries use to achieve their objectives during an attack, such as establishing command and control (C2) channels or delivering payloads via phishing emails. In this scenario, the attacker uses a non-default beacon profile in Cobalt Strike, sends a malicious document via email, and establishes a C2 channel once the victim interacts with the document, all of which are examples of adversary techniques.

In Splunk, field extractions are essential for transforming raw log data into structured fields that are easier to work with during analysis. When the question refers to an analyst identifying helpful information in the raw logs that assists them in determining suspicious activity, the most effective way to streamline this process is throughfield extraction. This allows the Splunk system to automatically parse and tag the necessary data, making it more accessible for searches, dashboards, and alerts.

Let’s break down whyoption A: Create a field extraction for this informationis the best approach:

Field Extraction Overview:

Field extraction is a process within Splunk that takes unstructured log data and converts it into structured fields.

This makes it possible to directly query and display these fields, allowing analysts to quickly find and use relevant data in their investigations.

For example, if the logs contain IP addresses, user IDs, file names, or activity types, extracting these fields enables the analyst to filter and correlate data much more effectively without manually scanning the raw logs.

Why Field Extraction?

In this case, the question suggests that the raw logs contain information that helps determine whether activity is malicious. By creating field extractions for the relevant data points, analysts can use those structured fields to build queries and visualizations, drastically speeding up analysis time.

Analysts can write custom Splunk queries to isolate events that meet specific conditions, such as matching specific cloud sharing activities associated with risk notables.

Field extraction improves not only real-time analysis but also supports retrospective analysis and incident correlation across multiple events.

Comparison to Other Options:

Option B: Add this information to the risk message– While adding more context to a risk message could be useful for reviewing individual alerts, it doesn’t improve the efficiency of log analysis. The analyst still would need to go back and manually inspect raw logs for more detailed data.

Option C: Create another detection for this information– Creating additional detections adds more rules, but doesn't solve the fundamental issue of having raw logs that aren’t easily searchable. You can only build effective detections when you have structured data available.

Option D: Allowlist more events based on this information– Allowlisting is generally used to reduce noise or irrelevant logs, but it doesn't help extract the necessary details for analysis. It may reduce unnecessary alerts, but won’t help analyze the suspicious events that do arise.

Cybersecurity Defense Analyst Best Practices:

Field extractionsshould be created for any important log source or data point, especially when handling complex or multi-part log entries (e.g., cloud sharing logs). This ensures logs are searchable and actionable, allowing for faster identification of anomalies and malicious activity.

Analysts should collaborate with engineers to ensure these extractions are tuned and validated. The extraction should be tailored to isolate the fields most relevant for identifying suspicious activity.

Once fields are extracted, analysts can create dashboards, real-time alerts, or retrospective searches based on the structured data for more effective incident response.

References:

Splunk Documentation: Field Extraction in Splunk

Cybersecurity defense techniques emphasize the importance of making log data actionable, which aligns with common practices in Incident Detection & Response (IDR) environments. Structured data is key to this effort, and field extraction is a critical part of transforming raw logs into useful intelligence

According to Splunk CIM (Common Information Model) documentation, thesrc_userfield in the Authentication Data Model represents the user who initiated an action, including privilege escalation. This field is used to track the source user responsible for generating an authentication event, which is critical in understanding and responding to potential security incidents involving privilege escalation. The other fields likedest_userorusernamehave different roles, focusing on the target of the action or the general username involved.

Top of Form

Bottom of Form