Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects high-volume file modifications or renames performed by a single process over a short window, affecting many unique file paths. This behavioral pattern is highly indicative of ransomware activity attempting to encrypt data for impact.
Detects anomalous user-mode processes requesting the SeLoadDriverPrivilege token privilege, which is essential for loading the EnCase driver (EEDbg.sys) into the kernel. This activity is indicative of a Bring Your Own Vulnerable Driver (BYOVD) attack using the EnCase driver.
This rule detects files matching known SHA256 hashes associated with the VoidLink malware framework. This is a high-fidelity indicator with a very low chance of false positives.
Detects modifications to the .vscode/extensions.json file which may be used by attackers to recommend malicious extensions to victims opening the workspace. Attackers can abuse this in conjunction with automated keystrokes to bypass warnings and force extension installations.
This rule detects the presence of files on devices that match known ransomware SHA256 hashes. It filters out common system processes (explorer.exe, svchost.exe, system.exe) as initiating processes to reduce false positives.
Identifies characteristics of compiled Go binaries (e.g., executing from temp with specific build path signatures in memory) taking malicious actions. This rule specifically looks for process execution of an executable, combined with network connections on port 445 (SMB), and the creation or modification of files ending with '.gentlemen'.
Detects files or processes matching SHA256 indicators published by Google Threat Intelligence Group for the INFINITERED campaign. The hashes cover the help.php persistence component, credential harvesters, backdoors, and droppers. A match should be treated as a high-confidence indicator of compromise and investigated immediately.
This rule detects unauthorized access, creation, or modification of browser-specific sensitive credential files (such as 'Login Data' or 'cookies.sqlite') by processes that are not recognized web browsers or trusted update services. This behavior is a common indicator of information-stealer malware attempting to harvest session cookies and stored credentials.
This rule detects potential ransomware activity by identifying the rapid encryption of multiple common document and database file types, indicated by the '.prinzeugen' extension. It specifically looks for at least 20 such files being created or modified within a 10-minute window on a single device.
Shebangs (#!) are native to Unix-like operating systems (macOS and Linux). Standard Windows consoles (Command Prompt and PowerShell) do not natively use them. However, they do work on Windows when using tools such as the Python Launcher, Git Bash, Cygwin, or Unix-like environments such as WSL. In simple terms, a Shebang tells the operating system which interpreter should execute a script. For example: #!/usr/bin/python3
Distinct scripts can not look dangerous based on their extension, but they are still executable files. In environments with macOS, Linux, WSL, Git Bash or Python Launcher, this can help to identify scripts renamed to hide their real purpose.
Distinct scripts can not look dangerous based on their extension, but they are still executable files. In environments with macOS, Linux, WSL, Git Bash or Python Launcher, this can help to identify scripts renamed to hide their real purpose.
This rule detects the creation or modification of executable files (.com, .exe, .scr, .pif, .bat, .cmd) in common user directories (Documents, Downloads, Desktop) where the initiating process is a legitimate application like explorer.exe, winrar.exe, or 7z.exe. This pattern is often used in phishing attacks where malicious executables are disguised as benign documents.
Detects manual mapping of SbieDll.bin into memory.
This rule detects the execution or file interaction of known local AI/Large Language Model tools (e.g., Ollama, LM Studio, GPT4All) when initiated by non-interactive system processes (such as services.exe, svchost.exe, or lsass.exe) or under system/network service account contexts. This behavior is indicative of unauthorized local model staging or enumeration within a compromised environment.
This rule detects the execution or file interaction of known local AI/Large Language Model tools (e.g., Ollama, LM Studio, GPT4All) when initiated by non-interactive system processes (such as services.exe, svchost.exe, or lsass.exe) or under system/network service account contexts. This behavior is indicative of unauthorized local model staging or enumeration within a compromised environment.
Detects files with suspicious double extensions (e.g., .exe.txt, .dll.txt) or .scr extension, which can indicate an attempt to masquerade malicious executables or scripts as benign text files or screensavers. The rule excludes files in the System32 directory to reduce false positives.
Identifies the execution of a specific decoy PDF document, '000b67d70f3876965bb09fd37164b7ccrezervaci.pdf', within 5 minutes of its creation. This activity is associated with the 'Dragon Weave' campaign, where the document is used as a lure to distract the victim during an infection.
This rule monitors file system events for the creation of files with common web shell names (e.g., shell.php, cmd.php) within known web server directory paths (e.g., wwwroot, inetpub). The detection of these specific file names in directories typically used for serving web content is a strong indicator of a potential web shell deployment.
Detects the creation of executable files (.exe, .com, .scr, .vbs, .js) that contain financial-themed keywords (e.g., GST, NEFT, RTGS, IMPS, Banking) in their filename. This pattern is commonly used in social engineering and phishing attacks to trick users into executing malicious payloads disguised as legitimate banking or financial documents.
Detects patterns indicative of double extortion ransomware attacks, specifically the staging of large volumes of archived data followed by suspicious command and control (C2) communications. The rule identifies the creation, modification, or movement of multiple large archive files (RAR, 7z, ZIP, TAR, GZ, CAB) in common temporary or system directories, and correlates this activity with outbound network connections to known C2 indicators such as Tor/I2P/VPN/proxy services or non-RFC1918 IP addresses.
This rule detects potential exploitation attempts targeting REDCap, specifically looking for file events involving 'help.php' or 'Upgrade.php', or network events where the remote URL contains 'REDCAP-TOKEN'. These indicators suggest an attacker might be trying to exploit known vulnerabilities or exfiltrate data from a REDCap instance.
This rule identifies indicators and behaviors associated with KongTuke and PS1Bot campaigns. It specifically looks for network connections to known malicious IPs, domains, and URI paths, as well as the execution or presence of files with known malicious SHA256 hashes associated with these campaigns. The original description mentions 'finger.exe abuse, scheduled task and registry persistence, dynamic C# compilation for keylogging/screen capture, and suspicious PowerShell download cradles', but the current KQL rule only covers network and file/process IOCs.
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