SPLK-5001 Splunk Certified Cybersecurity Defense Analyst Questions and Answers

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.

TheInvestigation Managementframework in Splunk Enterprise Security (ES) is specifically designed to help analysts manage the lifecycle of security incidents. This framework allows for the identification of incidents from aggregated notable events, and provides tools to manage incident ownership, track the triage process, and monitor the state or status of ongoing investigations.

Investigation Managementoffers workflows to assign incidents, add comments, document findings, and close investigations, ensuring a structured response process.

TheNotable Eventframework refers to the generation of alerts based on correlation searches but does not provide incident lifecycle management.

Asset and Identityenrich data with contextual information but is not focused on incident management.

Adaptive Responserefers to automated actions but not the management framework itself.

Splunk’sEnterprise Security User Guidedetails Investigation Management as the central tool for orchestrating SOC response workflows and ensuring effective case management.

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.

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.

In most organizations, the Security Engineer is typically responsible for implementing new processes or solutions that have been selected to protect assets. This role involves the practical application of security tools, technologies, and practices to safeguard the organization’s infrastructure and data.

Role of Security Engineer:

Implementation:Security Engineers are tasked with the hands-on deployment and configuration of security systems, including firewalls, intrusion detection systems (IDS), and endpoint protection solutions. When a risk is identified, they are the ones who implement the necessary technological controls or processes to mitigate that risk.

Technical Expertise:Security Engineers possess the technical skills required to integrate new solutions into the existing environment, ensuring that they operate effectively without disrupting other systems.

Collaboration:While Security Architects design the overall security architecture and the SOC Manager oversees operations, the Security Engineer works on the ground, implementing the detailed aspects of the solutions.

Contrast with Other Roles:

Security Architect:Designs the security framework and architecture but does not usually perform the actual implementation.

SOC Manager:Oversees the security operations and might coordinate the response but does not directly implement new solutions.

Security Analyst:Monitors and analyzes security data, but typically does not implement new security systems.

When creating performant searches in Splunk, it is a best practice to utilize specific fields to return only the data that is required. This approach minimizes the amount of data processed and speeds up search performance. By explicitly specifying the fields of interest using commands likefields, you reduce the overhead on Splunk’s processing engine, leading to faster and more efficient queries. In contrast, using wildcards or overly broad searches can lead to slower performance due to the increased data volume being processed.

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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.

TheContinuous Monitoringcycle begins with theDefine and Predictphase, where the security team establishes what needs to be monitored (defining assets, risks, controls) and predicts potential threats and vulnerabilities. This foundational phase sets objectives and scope for the monitoring program.

Subsequent phases likeMonitor and Protect,Assess and Evaluate, andRespond and Recoverfollow the initial definition.

This phased approach aligns with frameworks such as NIST’s Risk Management Framework and Continuous Monitoring guidelines.

Splunk’s cybersecurity documentation highlights the importance of this first phase for establishing a proactive and informed security posture.

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.

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.

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 Common Information Model (CIM) in Splunk is a crucial component that allows for the normalization and standardization of data across various sources. By using CIM, disparate data sources can be mapped to a common schema, which makes it significantly easier to correlate and analyze data across different logs and systems.

Purpose of CIM:CIM provides a standardized format for fields and event types across various data sources in Splunk. This normalization allows analysts to use consistent field names and structures when performing searches, regardless of the original data source's format.

Benefit of Easier Correlation:One of the primary challenges in security operations is correlating data from different sources—like firewalls, intrusion detection systems (IDS), endpoint security solutions, and network logs—to identify potential security incidents. CIM facilitates this by ensuring that all relevant data adheres to a common schema, enabling seamless correlation and analysis. For example, CIM allows a security analyst to write a single query that can apply to data from multiple sources, simplifying the detection of complex threats.

How it Works:CIM is implemented through data models in Splunk, which act as a blueprint for mapping and transforming raw data into a structured format. These data models cover a wide range of security domains, such as authentication, network traffic, and malware, ensuring that data from different security tools can be easily integrated and analyzed together.

Use Cases:The primary use cases for CIM include:

Search and Reporting:Creating efficient and standardized searches that apply across multiple data sources.

Dashboards and Visualizations:Building dashboards that pull in data from various sources in a consistent manner.

Correlation Searches:Developing correlation searches that detect patterns or anomalies across different types of data, enhancing threat detection.

The log entry shows a suspicious HTTP POST request to a path /cgi-bin/shurdown/, which closely resembles a misspelled or crafted endpoint that attempts to trigger a server shutdown. The fact that the server unexpectedly shut down after this request strongly suggests aDenial of Service (DoS) attack, where the attacker is attempting to disrupt service availability.

ADoS attackaims to make a resource unavailable, often by crashing the service or overwhelming it.

The presence of a POST request targeting a CGI script for shutdown indicates exploitation of a vulnerability that causes service interruption.

Distributed denial of service (DDoS)involves multiple sources flooding a target, which is not indicated here.

Database injectionattacks would be visible as injection strings in parameters and target backend data layers, not server shutdown logs.

Cross-Site Scripting (XSS)involves injecting scripts into webpages viewed by users, unrelated to server crashes.

Splunk’sCybersecurity Defense Analyst guidehighlights log analysis as critical in identifying such attacks by correlating suspicious HTTP requests with service disruptions.

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.

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.

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.

The correct Splunk search that returns results in the most performant way isindex=foo host=i-478619733 | stats range(_time) as duration by src_ip | bin duration span=5min | stats count by duration, host. This search is optimized by:

Starting with the most specific search criteria (index and host) to reduce the data set.

Applying aggregation functions (stats) early, which helps minimize the amount of data processed in subsequent commands.

Usingbinto group data efficiently before performing further statistical calculations.

Search Optimization:

Efficient Indexing:By specifyingindex=fooandhost=i-478619733at the start, the search limits the scope of data that needs to be processed, which significantly improves performance.

Early Aggregation:Thestatscommand is used early in the search to aggregate data bysrc_ip, which reduces the volume of data passed to the next stages of the pipeline.

Use ofbin:Grouping durations withbinbefore performing a secondstatsaggregation reduces the number of unique values, making the final stats calculation more efficient.

Performance Considerations:

Order of Operations:Splunk processes search commands from left to right. Starting with a broad data retrieval and then narrowing down with stats and bin commands ensures that the least amount of data is processed in the final stages.

Avoiding Suboptimal Patterns:The other options either apply operations in a less efficient order or involve unnecessary steps that increase processing time and resource usage.

A threat hunt is an iterative process where a hypothesis is developed and tested against data in an environment to detect the presence of threats or adversarial tactics, techniques, and procedures (TTPs).

Understanding the Hypothesis:

The hypothesis here is that a threat actor might userundll32for proxy execution of malicious code and leverage Cobalt Strike for command and control (C2).

The hunt would involve looking for indicators of these specific activities in logs and artifacts like Sysmon logs, netflow, IDS alerts, and EDR data.

Search and Analysis:

The threat hunter performed an extensive search across multiple log sources and found no evidence of Cobalt Strike or the specific malicious activities hypothesized.

Evaluation of the Hypothesis:

If the hypothesis were proven true,the presence of Cobalt Strike or related artifacts would be detected.

However, the hypothesis was not proven; instead, the hunt provided strong evidence that Cobalt Strike and the hypothesized malicious activities are not present.

Successful Threat Hunt:

The goal of threat hunting is not always to find a threat but to gain confidence in the security posture of the environment.

Outcome Dcorrectly identifies that the hunt was successful because it provided strong evidence supporting the absence of the hypothesized threat, thus improving confidence in the organization's security.

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.

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.

TheCHMC (Cybersecurity Health Management Capability)framework was created specifically to assess and measure an organization's cybersecurity maturity. Unlike compliance frameworks that focus on specific regulatory requirements (e.g., PCI-DSS for payment card security, GDPR for data privacy, or FISMA for federal information security management), CHMC provides a structured maturity model that evaluates the effectiveness and sophistication of cybersecurity practices within an enterprise.

TheCHMCframework benchmarks capabilities across various domains such as governance, risk management, incident response, and security operations, enabling organizations to identify gaps and prioritize improvements systematically.

PCI-DSSis a compliance standard aimed at securing payment card data.

GDPRgoverns data protection and privacy for individuals in the EU.

FISMAmandates federal agencies to implement information security programs but does not itself provide a maturity model.

TheSplunk Cybersecurity Defense Analyst materialshighlight that maturity models like CHMC help organizations progress beyond basic compliance, fostering a culture of continuous improvement in cybersecurity posture.

Adaptive Response Actions (ARAs)in Splunk Enterprise Security enable analysts to initiate automated or semi-automated remediation workflows directly from ES dashboards or investigations without leaving the interface. When integrated with Splunk SOAR (Security Orchestration, Automation, and Response), ARAs can trigger playbooks designed to execute containment actions on compromised devices and simultaneously update the original investigation or notable event.

Anadaptive response actionis tightly integrated with ES findings and provides immediate feedback into the investigation workflow.

Event-level and field-level workflow actions may support initiating external processes but are less integrated or standardized than ARAs.

Alert actions typically trigger notifications, not complex remediation playbooks.

TheSplunk Enterprise Security documentationhighlights ARAs as a key component for orchestrated response enabling analysts to act decisively within the ES context, ensuring containment activities are both tracked and correlated with initial findings.

Themakeresultscommand in Splunk is used to generate a single-row result that can be used to create test data within a search pipeline. This command is particularly useful for testing and experimenting with SPL commands on a small set of synthetic data without relying on existing logs or events in the Splunk index. It is commonly used by analysts who want to test commands or SPL syntax before applying them to real data.

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.

Continuous Monitoring Cycle:This cycle is part of a broader security strategy that involves constantly assessing and managing the security state of an organization's information systems. The phases generally include defining metrics, collecting data, analyzing it, reporting findings, and implementing improvements.

Analyze and Report Phase:

Data Evaluation:In this phase, the data collected from various monitoring tools and sensors is thoroughly analyzed. Security analysts look for trends, anomalies, and indications of potential threats or vulnerabilities.

Reporting:After the analysis, a report is generated that highlights the findings, including any detected issues, their potential impact, and the current effectiveness of security measures.

Recommendations:Based on the analysis, the report usually includes suggestions for improvements, such as additional security controls, configuration changes, or policy updates. These recommendations are aimed at enhancing the organization's security posture and addressing any identified gaps or weaknesses.

Purpose of Recommendations:The goal of this phase is to ensure that the organization’s security measures are continuously improved based on the latest data and threat landscape. It is a critical step in maintaining an effective security program that adapts to new challenges.

Web Proxy Logsare the most direct and relevant data source for determining whether a user visited a malicious website. Proxy servers act as intermediaries for user HTTP/HTTPS requests and record detailed metadata about web traffic including URLs visited, timestamps, user IDs, and other HTTP headers.

Web Proxy Logsprovide explicit visibility into outbound web requests from users, which is essential for detecting visits to malicious domains or IPs.

Active Directory Logstrack authentication and directory service activities but do not record web browsing data.

Intrusion Detection Logsmonitor suspicious network or host behaviors but may not have precise records of web destinations.

Web Server Logslog incoming requests to a specific server but do not reflect user browsing outside that server.

Splunk’s security analyst documentation emphasizes leveraging proxy logs for user activity tracking and threat detection related to web-based threats.