EXPLORE DETECTIONS
SecretDumps Offline NTDS Dumping Tool
The following analytic detects the potential use of the secretsdump.py tool to dump NTLM hashes from a copy of ntds.dit and the SAM, SYSTEM, and SECURITY registry hives. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns and process names associated with secretsdump.py. This activity is significant because it indicates an attempt to extract sensitive credential information offline, which is a common post-exploitation technique. If confirmed malicious, this could allow an attacker to obtain NTLM hashes, facilitating further lateral movement and potential privilege escalation within the network.
ServicePrincipalNames Discovery with PowerShell
The following analytic detects the use of `powershell.exe` to query the domain for Service Principal Names (SPNs) using Script Block Logging EventCode 4104. It identifies the use of the KerberosRequestorSecurityToken class within the script block, which is equivalent to using setspn.exe. This activity is significant as it often precedes kerberoasting or silver ticket attacks, which can lead to credential theft. If confirmed malicious, attackers could leverage this information to escalate privileges or persist within the environment.
ServicePrincipalNames Discovery with SetSPN
The following analytic detects the use of `setspn.exe` to query the domain for Service Principal Names (SPNs). This detection leverages Endpoint Detection and Response (EDR) data, focusing on specific command-line arguments associated with `setspn.exe`. Monitoring this activity is crucial as it often precedes Kerberoasting or Silver Ticket attacks, which can lead to credential theft. If confirmed malicious, an attacker could use the gathered SPNs to escalate privileges or persist within the environment, posing a significant security risk.
Services Escalate Exe
The following analytic identifies the execution of a randomly named binary via `services.exe`, indicative of privilege escalation using Cobalt Strike's `svc-exe`. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process lineage and command-line executions. This activity is significant as it often follows initial access, allowing adversaries to escalate privileges and establish persistence. If confirmed malicious, this behavior could enable attackers to execute arbitrary code, maintain long-term access, and potentially move laterally within the network, posing a severe threat to the organization's security.
Services LOLBAS Execution Process Spawn
The following analytic identifies `services.exe` spawning a LOLBAS (Living Off the Land Binaries and Scripts) execution process. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events where `services.exe` is the parent process. This activity is significant because adversaries often abuse the Service Control Manager to execute malicious code via native Windows binaries, facilitating lateral movement. If confirmed malicious, this behavior could allow attackers to execute arbitrary code, escalate privileges, or maintain persistence within the environment, posing a severe security risk.
Set Default PowerShell Execution Policy To Unrestricted or Bypass
The following analytic detects changes to the PowerShell ExecutionPolicy in the registry to "Unrestricted" or "Bypass." It leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry modifications under the path *Software\Microsoft\Powershell\1\ShellIds\Microsoft.PowerShell*. This activity is significant because setting the ExecutionPolicy to these values can allow the execution of potentially malicious scripts without restriction. If confirmed malicious, this could enable an attacker to execute arbitrary code, leading to further compromise of the system and potential escalation of privileges.
Shai-Hulud 2 Exfiltration Artifact Files
Detects creation of exfiltration artifact files associated with Shai-Hulud 2.0 npm supply chain malware. The malware creates cloud.json, contents.json, environment.json, truffleSecrets.json, and actionsSecrets.json files containing harvested credentials from AWS, Azure, GCP, GitHub secrets, and environment variables. These files are staged before being pushed to attacker-controlled repositories.
Shai-Hulud Workflow File Creation or Modification
Detects creation or deletion of malicious GitHub Actions workflow files associated with Shai-Hulud worm variants on Linux or Windows endpoints. This includes the original shai-hulud-workflow.yml, the 2.0 backdoor discussion.yaml (enables command injection via GitHub Discussions on self-hosted runners named SHA1HULUD), and the secrets exfiltration workflow formatter_*.yml pattern. These files are used to exfiltrate credentials and propagate across repositories.
Shim Database File Creation
The following analytic detects the creation of shim database files (.sdb) in default directories using the sdbinst.exe application. It leverages filesystem activity data from the Endpoint.Filesystem data model to identify file writes to the Windows\AppPatch\Custom directory. This activity is significant because shims can intercept and alter API calls, potentially allowing attackers to bypass security controls or execute malicious code. If confirmed malicious, this could lead to unauthorized code execution, privilege escalation, or persistent access within the environment.
Shim Database Installation With Suspicious Parameters
The following analytic detects the execution of sdbinst.exe with parameters indicative of silently creating a shim database. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line arguments. This activity is significant because shim databases can be used to intercept and manipulate API calls, potentially allowing attackers to bypass security controls or achieve persistence. If confirmed malicious, this could enable unauthorized code execution, privilege escalation, or persistent access to the compromised system.
Short Lived Scheduled Task
The following analytic detects the creation and deletion of scheduled tasks within a short time frame (less than 30 seconds) using Windows Security EventCodes 4698 and 4699. This behavior is identified by analyzing Windows Security Event Logs and leveraging the Windows TA for parsing. Such activity may indicate lateral movement or remote code execution attempts by adversaries. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or execution of malicious payloads, necessitating prompt investigation and response by security analysts.
Short Lived Windows Accounts
The following analytic detects the rapid creation and deletion of Windows accounts within a short time frame of 1 hour. It leverages the "Change" data model in Splunk, specifically monitoring events with result IDs 4720 (account creation) and 4726 (account deletion). This behavior is significant as it may indicate an attacker attempting to create and remove accounts quickly to evade detection or gain unauthorized access. If confirmed malicious, this activity could lead to unauthorized access, privilege escalation, or further malicious actions within the environment. Immediate investigation of flagged events is crucial to mitigate potential damage.
SilentCleanup UAC Bypass
The following analytic detects suspicious modifications to the registry that may indicate a UAC (User Account Control) bypass attempt via the SilentCleanup task. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry changes in the path "*\\Environment\\windir" with executable values. This activity is significant as it can allow an attacker to gain high-privilege execution without user consent, bypassing UAC protections. If confirmed malicious, this could lead to unauthorized administrative access, enabling further system compromise and persistence.
Single Letter Process On Endpoint
The following analytic detects processes with names consisting of a single letter, which is often indicative of malware or an attacker attempting to evade detection. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions. This activity is significant because attackers use such techniques to obscure their presence and carry out malicious activities like data theft or ransomware attacks. If confirmed malicious, this behavior could lead to unauthorized access, data exfiltration, or system compromise. Immediate investigation is required to determine the legitimacy of the process.
SLUI RunAs Elevated
The following analytic detects the execution of the Microsoft Software Licensing User Interface Tool (`slui.exe`) with elevated privileges using the `-verb runas` function. This activity is identified through logs from Endpoint Detection and Response (EDR) agents, focusing on specific registry keys and command-line parameters. This behavior is significant as it indicates a potential privilege escalation attempt, which could allow an attacker to gain elevated access and execute malicious actions with higher privileges. If confirmed malicious, this could lead to unauthorized system changes, data exfiltration, or further compromise of the affected endpoint.
SLUI Spawning a Process
The following analytic detects the Microsoft Software Licensing User Interface Tool (`slui.exe`) spawning a child process. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process creation events where `slui.exe` is the parent process. This activity is significant because `slui.exe` should not typically spawn child processes, and doing so may indicate a UAC bypass attempt, leading to elevated privileges. If confirmed malicious, an attacker could leverage this to execute code with elevated privileges, potentially compromising the system's security and gaining unauthorized access.
SMB Traffic Spike
The following analytic detects spikes in Server Message Block (SMB) traffic connections, which are used for sharing files and resources between computers. It leverages network traffic logs to monitor connections on ports 139 and 445, and SMB application usage. By calculating the average and standard deviation of SMB connections over the past 70 minutes, it identifies sources exceeding two standard deviations from the average. This activity is significant as it may indicate potential SMB-based attacks, such as ransomware or data theft. If confirmed malicious, attackers could exfiltrate data or spread malware within the network.
Spike in File Writes
The following analytic detects a sharp increase in the number of files written to a specific host. It leverages the Endpoint.Filesystem data model, focusing on 'created' actions and comparing current file write counts against historical averages and standard deviations. This activity is significant as a sudden spike in file writes can indicate malicious activities such as ransomware encryption or data exfiltration. If confirmed malicious, this behavior could lead to significant data loss, system compromise, or further propagation of malware within the network.
Splunk App for Lookup File Editing RCE via User XSLT
The following analytic identifies the creation of lookup files in Splunk, which could indicate an attempt to exploit remote code execution via user-supplied XSLT. It leverages REST API queries to monitor the creation of these lookups, focusing on fields such as title, author, and access control lists. This activity is significant because it targets a known vulnerability in Splunk versions 9.1.x, potentially allowing attackers to execute arbitrary code. If confirmed malicious, this could lead to unauthorized code execution, compromising the integrity and security of the Splunk environment.
Splunk AppDynamics Secure Application Alerts
The following analytic is to leverage alerts from Splunk AppDynamics SecureApp, which identifies and monitors exploit attempts targeting business applications. The primary attack observed involves exploiting vulnerabilities in web applications, including injection attacks (SQL, API abuse), deserialization vulnerabilities, remote code execution attempts, LOG4J and zero day attacks. These attacks are typically aimed at gaining unauthorized access, exfiltrating sensitive data, or disrupting application functionality. Splunk AppDynamics SecureApp provides real-time detection of these threats by analyzing application-layer events and correlating attack behavior with known vulnerability signatures. This detection methodology helps the Security Operations Center (SOC) by: * Identifying active exploitation attempts in real-time, allowing for quicker incident response. * Categorizing attack severity to prioritize remediation efforts based on risk level. * Providing visibility into attacker tactics, including source IP, attack techniques, and affected applications. * Generating risk-based scoring and contextual alerts to enhance decision-making within SOC workflows. * Helping analysts determine whether an attack was merely an attempt or if it successfully exploited a vulnerability. By leveraging this information, SOC teams can proactively mitigate security threats, patch vulnerable applications, and enforce security controls to prevent further exploitation.
Splunk Authentication Token Exposure in Debug Log
The following analytic identifies exposed authentication tokens in debug logs within Splunk Enterprise. It leverages logs from the `splunkd` component with a DEBUG log level, specifically searching for event messages that validate tokens. This activity is significant because exposed tokens can be exploited by attackers to gain unauthorized access to the Splunk environment. If confirmed malicious, this exposure could lead to unauthorized data access, privilege escalation, and potential compromise of the entire Splunk infrastructure. Monitoring and addressing this vulnerability is crucial for maintaining the security and integrity of the Splunk deployment.
Splunk Code Injection via custom dashboard leading to RCE
The following analytic identifies attempts to exploit a vulnerability in Splunk Enterprise versions below 8.2.9, 8.1.12, and 9.0.2, where an authenticated user can execute arbitrary code via the dashboard PDF generation component. It detects this activity by analyzing events in the _internal index with the file=export parameter. This behavior is significant because it indicates a potential code injection attack, which could lead to remote code execution (RCE). If confirmed malicious, an attacker could gain unauthorized access, execute arbitrary commands, and potentially compromise the entire Splunk environment.
Splunk Enterprise KV Store Incorrect Authorization
The following analytic detects unauthorized attempts to reload Splunk KV Store collections via the REST API. It leverages internal index logs to identify POST requests to the `/servicesNS/nobody/search/admin/collections-conf/_reload` endpoint, focusing on status codes starting with '2'. This activity is significant as it may indicate improper permission handling, potentially leading to unauthorized deletion of KV Store collections. If confirmed malicious, this could result in data loss or unauthorized data manipulation, impacting the integrity and availability of critical Splunk data.
Splunk Information Disclosure on Account Login
This is a composed hunting search that looks for possible user enumeration attempts when SAML is enabled on a Splunk instance by capturing different responses from server.