Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects process execution with at least two command-line arguments commonly used by Qilin ransomware.
Detects modifications to a registry key which contain an IP address as data which is used by HoldingHands malware to update its C2 server IP address.
The following analytic detects suspicious usage of BitLockerToGo.exe, which has been observed being abused by Lumma stealer malware. The malware leverages this legitimate Windows utility to manipulate registry keys, search for cryptocurrency wallets and credentials, and exfiltrate sensitive data. This activity is significant because BitLockerToGo.exe provides functionality for viewing, copying, and writing files as well as modifying registry branches - capabilities that the Lumma stealer exploits for malicious purposes. If confirmed malicious, this could indicate an active data theft campaign targeting cryptocurrency wallets, browser credentials, and password manager archives. The detection focuses on identifying BitLockerToGo.exe execution patterns that deviate from normal system behavior.
The following analytic identifies the execution of rundll32.exe with the DLL function names "Start" and "StartW," commonly associated with Cobalt Strike payloads. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and process metadata. This activity is significant as it often indicates the presence of malicious payloads, such as Cobalt Strike, which can lead to unauthorized code execution. If confirmed malicious, this activity could allow attackers to inject shellcode, escalate privileges, and maintain persistence within the environment.
The analytic detects AMOS Stealer VM check activity on macOS. It identifies the execution of the "osascript" command along with specific commandline strings that include "set", "system_profiler", and either "VMware" or "QEMU". This activity is indicative of AMOS stealer attempting to determine if it is running within a virtual machine environment. If confirmed malicious, this behavior suggests the host is infected by the AMOS stealer, which could lead to arbitrary code execution, privilege escalation, information theft, or persistence, posing a significant security risk.
The following analytic detects the execution of suspicious command-line arguments commonly associated with Conti ransomware, specifically targeting local drives and network shares for encryption. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs that include command-line details. This activity is significant because it indicates a potential ransomware attack, which can lead to widespread data encryption and operational disruption. If confirmed malicious, the impact could be severe, resulting in data loss, system downtime, and potential ransom demands.
The following analytic detects the loading of DLL modules associated with the GraphicalProton backdoor implant, commonly used by SVR in targeted attacks. It leverages Sysmon EventCode 7 to identify specific DLLs loaded by processes. This activity is significant as it may indicate the presence of a sophisticated backdoor, warranting immediate investigation. If confirmed malicious, the attacker could gain persistent access to the compromised host, potentially leading to further exploitation and data exfiltration.
This rule detects activity associated with the WannaCry ransomware. It specifically looks for the creation of processes with image names commonly used by WannaCry variants (e.g., 'tasksche.exe', 'mssecsvc.exe', 'WanaDecryptor' in the image path) or command lines containing the WannaCry ransom note filename ('@Please_Read_Me@.txt').
The analytic detects file writes with extensions indicative of a SamSam ransomware attack. It leverages file-system activity data to identify file names ending in .stubbin, .berkshire, .satoshi, .sophos, or .keyxml. This activity is significant because SamSam ransomware is highly destructive, leading to file encryption and ransom demands. If confirmed malicious, the impact includes significant financial losses, operational disruptions, and reputational damage. Immediate actions should include isolating affected systems, restoring files from backups, and investigating the attack source to prevent further incidents.
This analytic detects the creation or connection to a named pipe associated with Trickbot malware. It specifically looks for Sysmon EventCodes 17 (Pipe Created) and 18 (Pipe Connected) where the PipeName matches the pattern "\\pipe\\*lacesomepipe". This activity is significant because Trickbot uses named pipes for inter-process communication, often for C2 communication, data exfiltration, and command execution. Detecting this behavior can help identify Trickbot infections, which could lead to persistence, arbitrary command execution, and sensitive information exfiltration.
The analytic detects the use of Wake-on-LAN commands associated with Ryuk ransomware. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific process and command-line activities. This behavior is significant as Ryuk ransomware uses Wake-on-LAN to power on devices in a compromised network, increasing its encryption success rate. If confirmed malicious, this activity could lead to widespread ransomware encryption across multiple endpoints, causing significant operational disruption and data loss. Immediate isolation and thorough investigation of the affected endpoints are crucial to mitigate the impact.
Detects known MonsterV2 malware samples based on their SHA256 file hashes. Detecting these hashes on endpoints can directly identify MonsterV2 infections.
The following analytic identifies a high frequency of process termination events on a computer within a short period. It leverages Sysmon EventCode 5 logs to detect instances where 15 or more processes are terminated within a 3-second window. This behavior is significant as it is commonly associated with ransomware attempting to avoid exceptions during file encryption. If confirmed malicious, this activity could indicate an active ransomware attack, potentially leading to widespread file encryption and significant data loss.
Detects a non-browser process launching a browser with automation flags, which subsequently connects to WhatsApp Web. This behavior is consistent with the Maverick banking trojan's use of Selenium and WPPConnect to hijack WhatsApp sessions for self-propagation.
The analytic detects modifications to files with extensions commonly associated with ransomware. It leverages the Endpoint.Filesystem data model to identify changes in file extensions that match known ransomware patterns. This activity is significant because it suggests an attacker is attempting to encrypt or alter files, potentially leading to severe data loss and operational disruption. If confirmed malicious, this activity could result in the encryption of critical data, rendering it inaccessible and causing significant damage to the organization's data integrity and availability.
Detects PhantomVAI Loader and its common payload, Katz Stealer. PhantomVAI is a .NET loader known for delivering various infostealers and uses VM detection techniques. Katz Stealer is an infostealer notable for its anti-CIS country checks to evade analysis.
Detects the execution of game_cache.exe, stats_db.exe, or save_data.exe from a randomly named subdirectory within specific AppData\Local folders (like SystemCache, WindowsCache, AppCache, etc.).
This YARA rule detects the BPFDoor backdoor, a sophisticated Linux-based malware. It identifies specific byte patterns (strings) associated with different versions of BPFDoor's packet loop, reverse shell functionality, and process name manipulation. The rule looks for two main versions of these components, ensuring a comprehensive detection of the malware's core functionalities.
The following analytic detects the creation or dropping of executable or script files in the root directory of a removable drive. It leverages data from the Endpoint.Filesystem datamodel, focusing on specific file types and their creation paths. This activity is significant as it may indicate an attempt to spread malware, such as ransomware, via removable media. If confirmed malicious, this behavior could lead to unauthorized code execution, lateral movement, or persistence within the network, potentially compromising sensitive data and systems.
Detects network connections to the Discord API from non-Discord processes, a behavior associated with the ChaosBot malware.
The analytic detects the creation of image files (PNG, JPG, BMP, GIF, TIFF) in the AppData\Roaming folder by processes that also have a file reference in the same folder. This behavior is commonly associated with malware, such as the Remcos RAT, which captures screenshots and stores them in the AppData folder before exfiltrating them to a command-and-control server. If confirmed malicious, this activity could indicate unauthorized data capture and exfiltration, compromising sensitive information and user privacy.
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