SPLK-5001 Exam Dumps - Splunk Certified Cybersecurity Defense Analyst

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.

NIST SP 800-137:This publication provides guidelines on continuous monitoring of information systems, detailing the processes involved, including the Analyze and Report phase.

Security Operations Center (SOC) Best Practices:Many SOC frameworks emphasize the importance of the Analyze and Report phase in

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.

Splunk Enterprise Security (ES) provides various features to enhance security monitoring, analysis, and incident response. One of the powerful features in Splunk ES isAnnotations. This feature allows security analysts to map and categorize correlation search results according to well-known industry frameworks such as the CIS Critical Security Controls, MITRE ATT&CK, and the Lockheed Martin Cyber Kill Chain®.

Purpose of Annotations:

Annotations help analysts understand and categorize security events by aligning them with recognized security frameworks. This alignment provides context, making it easier to understand the nature of threats and how they fit within broader threat models or attack strategies.

How Annotations Work:

When a correlation search in Splunk ES triggers an alert, Annotations can automatically tag the alert with relevant tactics, techniques, and procedures (TTPs) from frameworks like MITRE ATT&CK. This helps in categorizing the event within the context of known attack patterns, offering insights into potential next steps by an attacker and recommended defensive actions.

Annotations can be manually added or configured to be applied automatically based on the nature of the search results.

Integration with Frameworks:

MITRE ATT&CK:Annotations can map alerts to specific techniques and tactics in the MITRE ATT&CK framework, which provides a detailed knowledge base of adversary behaviors, tactics, and techniques.

CIS Critical Security Controls:These controls can also be mapped through annotations, allowing the organization to measure and improve its security posture against these controls.

Lockheed Martin Cyber Kill Chain®:This model focuses on the stages of a cyberattack, and annotations can help identify where in the kill chain a particular alert fits, providing a clearer understanding of the attack’s progression.

Annotations in Splunk ES:Practical Example:Consider a correlation search that detects unusual behavior indicating potential lateral movement within a network. If this alert is annotated with a reference to the MITRE ATT&CK framework, it might map to techniques like "T1021 - Remote Services," which is associated with the lateral movement tactic. This mapping not only categorizes the event but also helps in planning the next steps for containment and investigation.

Efficiency in Response:By aligning alerts with industry frameworks, annotations help in quickly identifying the nature and potential impact of a threat.

Consistency in Analysis:Provides a standardized method for categorizing and responding to alerts, ensuring that all analysts interpret and react to threats in a consistent manner.

Improved Reporting:Allows for better visualization and reporting of threats according to established frameworks, making it easier to communicate risks and actions to stakeholders.

Splunk Documentation:Annotations in Splunk ES

MITRE ATT&CK Framework:MITRE ATT&CK®

Lockheed Martin Cyber Kill Chain®:Cyber Kill Chain

CIS Critical Security Controls:CIS Controls

Why Annotations Are Important:References:

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.

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.

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.

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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In Splunk Enterprise Security, theRisk Event Timelineprovides a chronological view of risk events associated with a particular Risk Object, such as a user or device. This timeline helps analysts visualize and understand the sequence and nature of risk events over time, aiding in the investigation of security incidents.

Risk Event Timeline:

The Risk Event Timeline is accessible by clicking the risk event count associated with a Risk Object in the Incident Review dashboard. This action opens up the timeline view, which provides a detailed chronological perspective on how risk events have unfolded.

This feature is particularly useful for tracking the progression of threats and understanding the context of incidents.

Incorrect Options:

A. Running the Risk Analysis Adaptive Response action within the Notable Event:This option pertains to running a response action rather than visualizing risk events over time.

B. Via a workflow action for the Risk Investigation dashboard:Although workflow actions can lead to various dashboards, the specific visualization described is accessed via the Risk Event Timeline.

C. Via the Risk Analysis dashboard under the Security Intelligence tab in Enterprise Security:While this dashboard provides valuable insights into risk data, the specific chronological visualization is found in the Risk Event Timeline.

Splunk Documentation:Risk Event Timeline in Splunk Enterprise Security provides step-by-step details on how to access and interpret the timeline.

References:

The scenario describes an attack where thousands of failed login attempts are made using various usernames and passwords, which is indicative of aCredential Stuffingattack. This type of attack involves using lists of stolen credentials (usernames and passwords) obtained from previous data breaches to attempt to gain unauthorized access to user accounts. Attackers take advantage of the fact that many users reuse passwords across multiple sites. UnlikePassword Spraying(which tries a few common passwords against many accounts) orPassword Cracking(which tries to guess or decrypt passwords), credential stuffing leverages large datasets of valid credentials obtained from other breaches.

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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.

MITRE ATT&CK Framework:Understanding how threat actors utilize tactics like Cobalt Strike for C2 can be aligned with TTPs in the framework, helping to build effective hypotheses.

Threat Hunting Resources:Books like "The Threat Hunter's Handbook" often describe scenarios where proving a negative (i.e., the absence of a threat) is a valid and successful outcome of a hunt.

Outcome of the Threat Hunt:References:

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 log entry indicates aPOST /cgi-bin/shutdown/request, which suggests that a command was sent to shut down the server via a CGI script. This kind of activity is indicative of aDenial of Service (DoS) attackbecause it involves sending a specific command that causes the server to stop functioning or shut down. This is different from a Distributed Denial of Service (DDoS) attack, which typically involves overwhelming the server with traffic rather than exploiting a specific command.

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.

Splunk Documentation:Detailed information on the Risk Framework and how it integrates with other security features in Splunk ES.

References:

In Splunk, to filter users with over a thousand occurrences, the pipeline| stats count by user | where count > 1000 | sort - countis most effective. Thestats count by usercommand generates a count of occurrences for each user. Thewhereclause then filters out only those users who have more than 1000 occurrences. Finally,sort - countsorts the results in descending order by count. This approach is efficient for identifying outliers, such as users with a high number of events.

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.

Splunk Command Documentation:rare command usage for identifying uncommon values.

References:

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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