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.

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.

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.

Top of Form

Bottom of Form

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 incident response and cybersecurity operations, Mean Time to Respond (MTTR) is a key metric. It measures the average time it takes from when an alert is created to when it is resolved or closed. In the scenario, an analyst identifies a Risk Notable Event as a false positive and closes it; the time taken from the alert ' s creation to its closure is what MTTR measures. This metric is crucial in understanding how efficiently a security team responds to alerts and incidents, thus contributing to overall security posture improvement.

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.

An executable running from theC:\Windows\Tempdirectory is a significant red flag because temporary directories are often world writable, meaning any user or process can write files to them. This characteristic makes these directories an attractive target for attackers who want to drop, stage, and execute malware without worrying about restrictive file permissions.

Temp Directories Characteristics:

World Writable:Temporary directories likeC:\Windows\Tempare typically writable by all users, which reduces the complexity for an attacker to place and execute malicious files.

Lack of Permissions Control:Since these directories do not have strict permission controls, attackers can easily exploit them to execute malicious payloads without being hindered by file access restrictions.

Security Risks:

Malware Staging:Attackers often use temp directories to stage malware because they can avoid detection by traditional security controls that monitor more critical directories like system folders.

Persistence Mechanisms:Some malware will persist in these directories and execute from them each time the system starts or when a particular trigger is activated.

Privilege Escalation:In some cases, malicious files placed in temp directories can be executed by more privileged processes, leading to privilege escalation.

Investigation Importance:The fact that an executable is running fromC:\Windows\Tempwarrants further investigation to determine whether it is malicious. Analysts should check:

File Origin:How the file got there, which user or process created it.

Behavior:What the executable is doing, such as establishing network connections, modifying system settings, or interacting with other sensitive files.

Integrity:Whether the executable is a legitimate system file or a potential piece of malware.

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.

This scenario describes aSupply Chain Attack, where malicious code or components are introduced into software by a third-party vendor or supplier, which then becomes part of the legitimate software used within an organization. Such attacks compromise the trust in software supply chains and can cause widespread impact.

Third-Party Malwareis a more generic term and does not fully capture the supply chain context.

Account Takeoverinvolves unauthorized access to user accounts.

Ransomwareis malware that encrypts data and demands payment, unrelated to origin tracing here.

Splunk’s cybersecurity training andMITRE ATT & CKemphasize supply chain attacks as a high-risk vector, particularly given the increasing use of third-party software.

Data Model Acceleration (DMA)in Splunk is used to improve search performance by creating summarized, indexed versions of data models that enable much faster retrieval than querying raw indexed data directly. This acceleration is particularly beneficial for complex searches, dashboards, and reports based on large datasets.

DMA precomputes and stores data aggregates, allowing near real-time responses for repeated queries.

It does not normalize data—that function is handled by CIM and data models themselves.

DMA is unrelated to comparing algorithms or modeling response actions.

According toSplunk documentation, enabling acceleration on data models significantly reduces search latency and enhances user experience, especially in security operations with high volumes of data.