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

The correct order of the examples listed corresponds toTactic, Technique, Procedurein the TTP framework:

Tactic:The high-level goal or objective an adversary tries to accomplish. "Extend movement" (likely meant as "Lateral movement") or "Exploiting a remote service" are tactics that describewhatthe adversary wants to do.

Technique:The general method or approach used to achieve the tactic. "Exploiting a remote service" is a technique, detailing the type of action used in pursuit of the tactic.

Procedure:The specific implementation or instance of a technique. "Use EternalBlue to exploit a remote SMB server" is a concrete procedure, an exact exploit tool or method used.

This hierarchy is fundamental to frameworks likeMITRE ATT&CK, which guides how analysts categorize and investigate adversary behaviors.

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.

TheTERM()search command in Splunk allows an analyst to match a specific term exactly as it appears, even if it contains characters that are usually considered minor breakers, such as periods or underscores. By usingTERM(), the search engine treats everything inside the parentheses as a single term, which is especially useful for searching log data where certain values (like IP addresses or filenames) should be matched exactly as they appear in the logs.

Adaptive Response is a feature in Splunk's Enterprise Security (ES) framework that allows security teams to automate actions and responses based on alerts or notable events. This feature is pivotal for orchestrating automated incident response processes, reducing the time between detection and response, and integrating Splunk with external systems to trigger appropriate actions.

Purpose:Adaptive Response enables the automation of specific tasks or workflows based on security events detected by Splunk ES. For instance, it can trigger actions such as isolating a compromised host, blocking IP addresses, or enriching data by querying additional sources when a notable event occurs.

Mechanism:When a notable event is identified within the Splunk platform, Adaptive Response can execute a series of predefined actions. These actions can be configured within the Splunk interface, allowing them to run automatically or with manual approval depending on the organization's needs. This capability is essential for streamlining security operations, especially in environments where quick response is critical.

Integration with External Applications:One of the key features of Adaptive Response is its ability to integrate with third-party security tools and solutions. This integration extends the capabilities of Splunk by allowing it to interact with other systems likefirewalls, intrusion prevention systems (IPS), endpoint detection and response (EDR) tools, and ticketing systems. This ensures a coordinated and comprehensive defense mechanism.

Usage in Security Operations:Security analysts often rely on Adaptive Response for managing and automating common security tasks, such as:

Quarantine or isolate a hostin response to malware detection.

Trigger a full disk scanwhen suspicious activity is detected.

Notify relevant stakeholdersthrough ticketing systems or direct communication tools.

Update firewall rulesto block traffic from a suspicious IP address.

ThemetadataSPL command in Splunk can be used to retrieve various types of metadata information indexed in Splunk. To list the differentsourcetypes(i.e., the categorization of the incoming data), the analyst should use the argument metadata type=sourcetypes.

metadata type=sourcetypes returns a list of all sourcetypes currently indexed, which is essential for understanding what kinds of data are available.

metadata type=hosts lists hosts sending data but does not categorize data types.

metadata type=cdn and metadata type=assets are not valid or standard types for this command in Splunk.

This usage is documented in Splunk’s official search command reference and is fundamental for data management and onboarding processes.

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.

The fastest SPL (Search Processing Language) search in Splunk is one that leverages index and sourcetype constraints upfront to minimize the amount of data scanned, thereby reducing search latency significantly. According to theSplunk Cybersecurity Defense Analyst Study Guide, searches that specifyindexandsourcetypein the base search filter data more efficiently by restricting the search scope immediately at the indexing layer before any processing occurs. This contrasts with searches that filter fields only after the raw data is retrieved, which is less efficient.

Option D explicitly specifies theindex-networkandsourcetype=netflow, combined with the exact field filterssrc_ip=1.2.3.4,src_port=2938, andprotocol=top. This precise filtering directly reduces the dataset Splunk has to scan.

Options A and C use theindex-networkbut filter some fields after the initial search (e.g., using search src_ip=1.2.3.4 after stats aggregation), causing unnecessary processing overhead.

Option B lacks any index or sourcetype specification, meaning Splunk performs a much broader search across all indexes and data, which is slower.

TheSplunk Cybersecurity Defense Analyst official documentationemphasizes that applying early filtering with index and sourcetype limits is crucial for search performance, particularly in high-volume network data scenarios.

The primary difference between a Distributed Denial of Service (DDoS) attack and a Denial of Service (DoS) attack is in the source of the attack. ADDoSattack involves multiple compromised systems (often part of a botnet) attacking a single target, overwhelming it with traffic or requests. In contrast, aDoSattack typically involves a single source attacking the target. The goal of both attacks is to make a service unavailable, but DDoS attacks are usually more difficult to defend against because of their distributed nature.

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.

The Splunk Security Content library, which includes apps like ESCU (Enterprise Security Content Update) and SSE (Splunk Security Essentials), primarily consists of Dashboards, Reports, and Correlation Searches.Validated architecturesare not a component of these content libraries. Instead, validated architectures refer to predefined, best-practice designs for deploying and configuring Splunk in a way that ensures optimal performance and scalability, which is separate from the content libraries focused on delivering security detections and visualizations.

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TheRisk Frameworkin Splunk Enterprise Security is designed to raise the threat profile of individuals or assets based on their activities. It allows security teams to assign risk scores to users or devices that engage in suspicious or anomalous behaviors, making it easier to identify entities that may require further investigation.

Risk Framework:

This framework aggregates risk events and calculates risk scores that help in prioritizing alerts and focusing on high-risk entities within the organization.

By identifying and raising the profile of entities involved in suspicious activities, it enables proactive threat detection and response.

Incorrect Options:

A. Threat Intelligence Framework:Integrates threat intelligence feeds but does not directly handle risk scoring of assets.

C. Notable Event Framework:Manages notable events but is not focused on risk profiling.

D. Asset and Identity Framework:Manages asset and identity data, linking them with events, but does not perform risk scoring.

In a successful Continuous Monitoring initiative, when an analyst identifies the need for more context or additional information, the request typically escalates to aSecurity Engineer. Security Engineers are responsible for the integration and configuration of additional data sources, and they can alter correlation rules or enhance data ingestion pipelines to provide the necessary context for analysts.

Security Engineer:

Manages and optimizes security tools and systems, including SIEM (like Splunk), and ensures that the necessary data sources are integrated into the monitoring environment.

Responsible for creating and tuning correlation rules and maintaining the infrastructure required for continuous monitoring.

Incorrect Options:

A. SOC Manager:Oversees the overall operations of the SOC but does not typically handle the technical integration of data sources.

B. Security Analyst:Primarily focuses on monitoring, detecting, and responding to security incidents, rather than configuring systems.

D. Security Architect:Focuses on the overall design of the security infrastructure, not on the day-to-day integration of data sources.

For creating a custom dashboard focused on typosquatting, theNew Domain Analysisdashboard in Splunk Enterprise Security (ES) would be a relevant starting point. Typosquatting typically involves the registration of domains similar to legitimate domains to deceive users, which is closely related to the analysis of newly registered or observed domains. This dashboard already includes tools and visualizations for monitoring and analyzing domain name activity, which can be adapted for the specific needs of monitoring for typosquatting.

In Splunk, therarecommand is used to return the least common values in a field. This command is particularly useful for anomaly detection, as it helps identify unusual or infrequent occurrences in a dataset, which may indicate potential security issues.

rare Command:

This command works by identifying values that appear infrequently within a specified field. It’s a powerful tool for Cyber Defense Analysts who are looking for anomalies that could signify malicious activities.

Incorrect Options:

A. least:This is not a valid Splunk command.

B. uncommon:This is not a valid Splunk command.

D. base:This is not a relevant command for finding the least common values.

NetFlow data is a powerful data source for monitoring and analyzing network traffic patterns within an organization. It provides detailed information about the flow of data between devices on a network, including source and destination IP addresses, ports, and protocols. By analyzing NetFlow data, security analysts can detect unusual communication patterns that may indicate malicious activity, such as lateral movement, data exfiltration, or communication with command and control servers. Other options like EDS (Endpoint Detection Systems), Email, and IAM (Identity and Access Management) are also valuable, but NetFlow is specifically designed for network traffic analysis.

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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.

TheSecurity Architectis primarily responsible for designing and selecting the security infrastructure, including tools and technologies that security analysts use to perform their tasks effectively. According to theSplunk Cybersecurity Defense Analyst Study Guide, the Security Architect role involves developing security solutions that align with organizational policies, compliance requirements, and operational needs. This role encompasses understanding both technical and business risks and ensuring that the deployed systems provide the necessary coverage for threat detection, prevention, and response.

TheSecurity Architectdevelops frameworks, specifies hardware and software components, and works closely with security engineers and SOC teams to implement these designs.

TheSecurity Engineertypically implements and maintains the infrastructure but does not design the overarching architecture.

TheSOC Manageroversees operations and personnel but does not focus on tool selection or infrastructure design.

TheThreat Intelligence Analystfocuses on gathering and analyzing threat data to inform defensive measures rather than designing infrastructure.

TheSplunk documentation and trainingexplicitly cite that security architecture involves planning and integrating security technologies and systems to create effective defense layers, supporting analyst workflows.

Abaselineis a representation or model of normal network activity, capturing expected patterns and behaviors over time. It serves as a reference point against which anomalies and deviations can be detected. By establishing a baseline, security analysts can identify unusual activities that might indicate security incidents.

Baselineinvolves statistical analysis of historical data to define normal ranges for metrics like traffic volume, connection rates, or login times.

Clusterrefers to grouping similar data points, often used in anomaly detection but not synonymous with a model of normal activity.

Time seriesis a sequence of data points indexed in time order, useful for monitoring trends but not specifically a model of normalcy.

Data modelrefers to an abstract schema for organizing data, such as Splunk’s CIM data models.

TheSplunk Cybersecurity Defense Analyst Study Guidehighlights baselining as a fundamental technique in anomaly detection and network security monitoring.

When an event is identified as suspicious but is expected or normal behavior within the environment, the appropriate disposition to assign isBenign. This categorization distinguishes such events from true security incidents or false positives, providing analysts with clarity on what to expect in their environment.

ATrue positiveindicates a confirmed security incident or threat that requires further investigation or response.

False positiverefers to an alert incorrectly triggered by benign activity that resembles malicious behavior but is not.

Informationaldisposition is typically reserved for events that provide data without implying suspicion or threat.

Benignis used for events that may look suspicious but are accepted as normal or expected in the specific environment context, helping reduce noise and improve analyst efficiency.

TheSplunk Cybersecurity Defense Analyst documentationadvises SOC teams to clearly define and apply dispositions consistently to ensure proper event triage and avoid alert fatigue.

TheAccess dashboardsin Splunk Enterprise Security focus on authentication, login activity, access controls, and related security events. These dashboards provide analysts with insights into successful and failed authentications, anomalous access patterns, and identity-related events.

Audit dashboardsgenerally focus on compliance and audit logs.

Asset and Identity dashboardsprovide broader context about users and devices but are not specifically focused on authentication events.

Endpoint dashboardsconcentrate on host and endpoint telemetry such as process execution and file activity.

Splunk’sEnterprise Security User Guideclearly identifies Access dashboards as the primary interface for monitoring and investigating authentication and access behaviors.

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.

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This scenario is an example of aFalse Negativebecause the detection mechanisms failed to generate alerts for a brute-force attack due to a misconfiguration—specifically, the exclusion of Linux data from the detection searches. A False Negative occurs when a security control fails to detect an actual malicious activity that it is supposed to catch, leading to undetected attacks and potential breaches.

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.

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Thefile_aclfield, which contains access controls associated with files affected by an event, is part of theEndpointdata model in Splunk. The Endpoint data model is designed to include information related to file access, process activity, and user activity on endpoints. Fields likefile_aclare critical for understanding permissions and potential security risks associated with file access and manipulation, which are key aspects of endpoint security monitoring.

InSplunk SOAR, the primary feature used to automate security workflows isPlaybooks. Playbooks are collections of automated and orchestrated tasks designed to streamline security processes such as alert triage, enrichment, containment, and remediation. By automating these routine tasks, playbooks enable analysts to focus on higher-level analysis and investigations.

Workbooksare documentation or guided investigations but are not automation tools.

Analytic Storiesare a feature in Splunk Enterprise Security to visualize complex attack scenarios, not workflow automation.

Adaptive Actionsare specific automated responses triggered within Splunk ES but are part of the ES platform, not SOAR’s primary automation mechanism.

TheSplunk SOAR official documentationdefines playbooks as modular, reusable workflows that can integrate multiple security tools and processes.

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.

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.