Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic detects the execution of the 'shred' command on a Linux machine, which is used to overwrite files to make them unrecoverable. It leverages data from Linux Auditd, focusing on process names and command-line arguments. This activity is significant because the 'shred' command can be used in destructive attacks, such as those seen in the Industroyer2 malware targeting energy facilities. If confirmed malicious, this activity could lead to the permanent destruction of critical files, severely impacting system integrity and data availability.
The following analytic detects the execution of msbuild.exe from a non-standard path. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that deviate from typical msbuild.exe locations. This activity is significant because msbuild.exe is commonly abused by attackers to execute malicious code, and running it from an unusual path can indicate an attempt to evade detection. If confirmed malicious, this behavior could allow an attacker to execute arbitrary code, potentially leading to system compromise and further malicious activities.
The following analytic detects the execution of renamed instances of msbuild.exe. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names within the Endpoint data model. This activity is significant because msbuild.exe is a legitimate tool often abused by attackers to execute malicious code while evading detection. If confirmed malicious, this behavior could allow an attacker to execute arbitrary code, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.
The analytic identifies the use of `sqlite3` querying the MacOS preferences to determine the original URL from which a package was downloaded. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions involving `LSQuarantine`. This activity is significant as it is commonly associated with MacOS adware and other malicious software. If confirmed malicious, this behavior could indicate an attempt to track or manipulate downloaded packages, potentially leading to further system compromise or persistent adware infections.
This detection identifies when an Active Directory Group Policy is deleted using the Group Policy Management Console. Deleting Group Policy Objects (GPOs) can be a legitimate administrative action, but it can also be used by adversaries to remove security controls, disable logging, or clean up traces of their activity. Monitoring for GPO deletions is crucial for maintaining the integrity of an Active Directory environment.
This rule detects when the owner of an Active Directory object is updated. Changing an object's owner grants full control over that object, which can be a significant privilege escalation or a precursor to hiding an AD object. The rule specifically looks for EventCode 5136 in Windows Security Event Logs, filtering for changes in the 'owner' attribute.
The following analytic detects the execution of the Windows OS tool cmdkey.exe, which is often abused by post-exploitation tools like winpeas, commonly used in ransomware attacks to list stored usernames, passwords, or credentials. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This activity is significant as it indicates potential credential harvesting, which can lead to privilege escalation and persistence. If confirmed malicious, attackers could gain unauthorized access to sensitive information and maintain control over compromised systems for further exploitation.
The following analytic detects the use of AppCmd.exe to disable HTTP logging on IIS servers. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution events where AppCmd.exe is used with specific parameters to alter logging settings. This activity is significant because disabling HTTP logging can help adversaries hide their tracks and avoid detection by removing evidence of their actions. If confirmed malicious, this could allow attackers to operate undetected, making it difficult to trace their activities and respond to the intrusion effectively.
The following analytic detects the execution of DiskCryptor, identified by the process names "dcrypt.exe" or "dcinst.exe". This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names. DiskCryptor is significant because adversaries use it to manually encrypt disks during an operation, potentially leading to data inaccessibility. If confirmed malicious, this activity could result in complete disk encryption, causing data loss and operational disruption. Immediate investigation is required to mitigate potential ransomware attacks.
The analytic identifies potential Kerberos ticket forging attacks, specifically the Diamond Ticket attack. This is detected when a user logs into a host and the GroupMembership field in event 4627 indicates a privileged group (e.g., Domain Admins), but the user does not actually belong to that group in the directory service. The detection leverages Windows Security Event Log 4627, which logs account logon events. The analytic cross-references the GroupMembership field from the event against a pre-populated lookup of actual group memberships. Any discrepancies between the events GroupMembership and the lookup indicate potential ticket forging. Kerberos ticket forging, especially the Diamond Ticket attack, allows attackers to impersonate any user and potentially gain unauthorized access to resources. By forging a ticket that indicates membership in a privileged group, an attacker can bypass security controls and gain elevated privileges. Detecting such discrepancies in group memberships during logon events can be a strong indicator of this attack in progress.
The analytic detects the shutdown of the Windows Event Log service by leveraging Windows Event ID 1100. This event is logged every time the service stops, including during normal system shutdowns. Monitoring this activity is crucial as it can indicate attempts to cover tracks or disable logging. If confirmed malicious, an attacker could hide their activities, making it difficult to trace their actions and investigate further incidents. Analysts should verify if the shutdown was planned and review other alerts and data sources for additional suspicious behavior.
This analytic detects EventLog reconnaissance activity using utilities such as `wevtutil.exe`, `wmic.exe`, PowerShell cmdlets like `Get-WinEvent`, or WMI queries targeting `Win32_NTLogEvent`. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. These tools are often used by adversaries to extract usernames, IP addresses, session data, and event information for credential access or situational awareness during lateral movement. While these utilities are legitimate, execution with specific arguments or targeting sensitive logs like `Security`, `PowerShell`, or specific EventIDs (e.g., 4624, 4778) can indicate malicious intent. If confirmed malicious, this behavior could allow an attacker to extract sensitive info and potentially have leveraged access or move laterally.
The following analytic identifies command-line activity querying the registry for Security Support Providers (SSPs) related to Local Security Authority (LSA) protection and configuration. This detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on processes accessing specific LSA registry paths. Monitoring this activity is crucial as adversaries and post-exploitation tools like winpeas may use it to gather information on LSA protections, potentially leading to credential theft. If confirmed malicious, attackers could exploit this to scrape password hashes or plaintext passwords from memory, significantly compromising system security.
The following analytic detects the execution of the SOAPHound binary (`soaphound.exe`) with specific command-line arguments. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, command-line arguments, and other process-related metadata. This activity is significant because SOAPHound is a known tool used for credential dumping and other malicious activities. If confirmed malicious, this behavior could allow an attacker to extract sensitive information, escalate privileges, or persist within the environment, posing a severe threat to organizational security.
The following analytic detects `wmiprvse.exe` spawning a LOLBAS execution process. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process creation events where `wmiprvse.exe` is the parent process and the child process is a known LOLBAS binary. This activity is significant as it may indicate lateral movement or remote code execution by an adversary abusing Windows Management Instrumentation (WMI). 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.
The analytic detects the creation of a symlink to a shadow copy, which may indicate credential dumping attempts. It identifies processes executing commands containing "mklink" and "HarddiskVolumeShadowCopy". This activity is significant because attackers often use this technique to manipulate or delete shadow copies, hindering system backup and recovery efforts. If confirmed malicious, this could prevent data restoration, complicate incident response, and lead to data loss or compromise. Analysts should review the process details, user, parent process, and any related artifacts to identify the attack source.
This analytic identifies the abuse of the right-to-left override (RTLO) character (U+202E) in process names. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs and command-line data. This activity is significant because adversaries use the RTLO character to disguise malicious files or commands, making them appear benign. If confirmed malicious, this technique can allow attackers to execute harmful code undetected, potentially leading to unauthorized access, data exfiltration, or further system compromise.
The analytic identifies the disabling of the firewall using the netsh application. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions that include keywords like "firewall," "off," or "disable." This activity is significant because disabling the firewall can expose the system to external threats, allowing malware to communicate with its command and control (C2) server. If confirmed malicious, this action could lead to unauthorized data exfiltration, further malware downloads, and broader network compromise.
The following analytic identifies a suspicious series of command-line executions attempting to disable multiple services. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes where "sc.exe" is used with parameters like "config" or "Disabled" within a short time frame. This activity is significant as it may indicate an adversary's attempt to disable security or other critical services to further compromise the system. If confirmed malicious, this could lead to the attacker achieving persistence, evading detection, or disabling security mechanisms, thereby increasing the risk of further exploitation.
The following analytic identifies excessive usage of `taskkill.exe`, a command-line utility used to terminate processes. The detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on instances where `taskkill.exe` is executed ten or more times within a one-minute span. This behavior is significant as adversaries often use `taskkill.exe` to disable security tools or other critical processes to evade detection. If confirmed malicious, this activity could allow attackers to bypass security defenses, maintain persistence, and further compromise the system.
The analytic detects the presence of any version of the 3CXDesktopApp, also known as the 3CX Desktop App, on Mac or Windows systems. It leverages endpoint data to identify instances of the application running. This activity is significant because 3CX has identified vulnerabilities in versions 18.12.407 and 18.12.416, which could be exploited by attackers. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or further compromise of the affected systems.
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