Practice Free SPLK-5001 Splunk Certified Cybersecurity Defense Analyst Exam Questions Answers With Explanation

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.

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.

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.

In Splunk,default metadatarefers to automatically assigned attributes associated with each event at indexing time that help identify and organize data. These include:

Source: The origin of the data (file, network port, etc.)

Timestamps: The time the event occurred, extracted from the event or assigned at ingestion

Host name: The name of the host generating the event

Event descriptionis not a default metadata field in Splunk. It is typically user-defined or derived from the event content and is not assigned automatically by Splunk.

TheSplunk documentationon event metadata clarifies these standard fields, which are crucial for search filtering and data organization.

According to Splunk’s Common Information Model (CIM) documentation, when investigating network alerts, the IP address of the host from which an attacker is moving (source) is typically stored in thesrc_ipfield. Thehostfield generally refers to the name of the host that logged the event,destrefers to the destination IP, andsrc_nt_hostrefers to the NetBIOS name of the source host. Thesrc_ipfield is specifically used to denote the source IP address in the context of network communication, which is critical for tracing lateral movement.

TheIdentity Centerdashboard in Splunk Enterprise Security is the primary interface for managing and reporting on user identities, including users currently on watchlists. This dashboard allows analysts to track user behavior, alerts, and notable events related to specific user identities, with the ability to view and manage watchlist membership.

Identity Centerprovides focused visibility into user-centric data and investigations.

Access Trackeris more general for access logs and authentication events but does not provide watchlist management.

Access CenterandIdentity Trackerare not standard dashboard names in Splunk ES.

TheSplunk Enterprise Security User Guiderecommends the Identity Center for watchlist monitoring and user-focused investigations.

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.

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.

In the context of theTTP (Tactics, Techniques, and Procedures)framework used in cybersecurity, the termProcedurerefers to the specific implementation or method used by an adversary to execute an attack or achieve an objective. Here, "LoudWiner" represents a particular malware or tool used by the adversary to hijack resources for crypto mining, which is an actualprocedure—the concrete steps or methods taken to accomplish the broader technique or tactic.

Tacticis the adversary’s goal or objective (e.g., resource hijacking for financial gain).

Techniqueis a general method used to achieve the tactic (e.g., crypto mining via malware).

Procedureis the specific variant or implementation of the technique (e.g., using LoudWiner malware).

Problemis not a recognized element in the TTP framework.

TheMITRE ATT&CK frameworkdefines procedures as real-world implementations of techniques by adversaries. Splunk’s cybersecurity analyst materials emphasize understanding these distinctions to better map observed adversary behavior.

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.

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.

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.

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.

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.

Outlier detection is a fundamental technique in anomaly detection used in cybersecurity and data science. The method identifies data points that deviate significantly from the established norm or clusters of typical behavior. Data points that falloutside high-density clusters(the groups of similar data) are labeled asanomaliesbecause they do not conform to expected patterns.

Anomaliesindicate potentially suspicious or malicious activities, such as unusual login times, unexpected network traffic, or data exfiltration attempts.

Inconsistenciesis a broader term but lacks the precise meaning used in clustering or anomaly detection.

Baselinedrefers to establishing normal behavior patterns rather than identifying deviations.

Non-conformativesis not a standard term in this context.

According to theSplunk Cybersecurity Defense Analyst Study GuideandSplunk Machine Learning Toolkit documentation, detecting anomalies through outlier detection algorithms (e.g., DBSCAN, isolation forest) is key to threat detection and investigation workflows.

Indicators of Compromise (IOCs) are artifacts that are used to identify potential malicious activity within a network or system. Common IOCs include domains, IP addresses, and file hashes that are associated with malicious activity. However, a specific password, while potentially sensitive, is not typically considered an IOC because it is more of a credential than an artifact indicating a compromise. IOCs are used to detect and respond to threats, while compromised credentials are a result of those threats.

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.

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.

AnIntrusion Detection System (IDS)typically sits at the network perimeter and is designed to detect suspicious traffic, including command and control (C2) traffic and other potentially malicious activities.

Intrusion Detection Systems:

IDS are deployed at strategic points within the network, often at the perimeter, to monitor incoming and outgoing traffic for signs of malicious activity.

These systems are configured to detect various types of threats, including C2 traffic, which is a key indicator of compromised systems communicating with an attacker-controlled server.

Incorrect Options:

A. Host-based firewall:This is more focused on controlling traffic at the endpoint level, not at the network perimeter.

B. Web proxy:Primarily used for controlling and filtering web traffic, but not specifically designed to detect C2 traffic.

C. Endpoint Detection and Response (EDR):Focuses on endpoint protection rather than monitoring network perimeter traffic.

Splunk SOAR (Security Orchestration, Automation, and Response) Playbooks are designed to automate repetitive and orchestratedresponse actions, such as containment or remediation on compromised systems. The use case oftaking containment action on a compromised hostfits perfectly, as playbooks execute sequences like isolating the host, killing processes, or blocking network communications automatically or with analyst approval.

Forming hypothesis for threat huntingis a manual, analytical process not suitable for automation via playbooks.

Creating persistent field extractionsis a data parsing task performed in Splunk searches or configurations, unrelated to SOAR playbooks.

Visualizing complex datasetsis a reporting and analytics task done with dashboards or apps, not SOAR workflows.

TheSplunk SOAR documentationexplicitly defines playbooks as automation workflows to accelerate incident response and reduce analyst workload on containment and investigation.

Thetstatscommand in Splunk is designed for highly efficient querying of large datasets because it operates primarily onindexed metadatarather than the full raw event data. Indexed metadata consists of pre-extracted, summarized information such as field values, timestamps, and host information, which is stored in a highly optimized format. This allowststatsto return results much faster than thestatscommand, which processes raw event data after retrieval.

tstatsqueries accelerated data models or index metadata directly, reducing disk I/O and CPU usage.

statsoperates on raw events, which can be expensive in terms of resources for large datasets.

The SQL-like syntax oftstats(Option C) is a convenience but not the reason for its performance benefits.

tstatsdoes not search raw logs for extracted fields; that is the domain of thestatscommand.

Splunk’s official documentation and theCybersecurity Defense Analyst Study Guideemphasize the importance oftstatsfor performance-optimized queries in security operations and large-scale data analysis.

Pyramid of Pain Overview:The Pyramid of Pain categorizes indicators based on how difficult they are for attackers to alter:

Hash Values (Low Impact):Attackers can easily change a file's hash by altering even a single byte, rendering this indicator obsolete.

IP Addresses, Domain Names (Moderate Impact):Slightly harder to change than hash values but still relatively easy for attackers to adapt.

TTPs (High Impact):Tactics, Techniques, and Procedures are the most difficult for attackers to alter because they involve the fundamental ways attackers operate. Detecting and responding to TTPs can significantly disrupt an attacker’s strategy.

Why Hash Values Are Least Effective:

Ease of Evasion:Attackers can quickly generate new hash values by modifying files, making it a weak indicator for continuous monitoring.

Short Lifespan:Once detected and blocked, a hash value is of limited use because attackers can simply recompile or pack the malware to create a new hash.

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,lookup tablesare the preferred method for enriching raw event data with additional contextual information such as ASN (Autonomous System Number) and IP ownership. By importing a lookup table that maps IP addresses to ASNs and owners, analysts can perform lookups during searches to append this valuable metadata.

Therexcommand is used for extracting patterns from raw text but does not provide enrichment.

oval commandsandmakersanitaare not valid Splunk commands related to ASN enrichment.

Splunk documentation and theCybersecurity Defense Analyst Study Guiderecommend configuring IP-to-ASN lookups to augment network security data for better attribution and threat hunting.