Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of MassLogger RAT components where the command line contains 'masslogger', 'mass.logger', or 'logger.exe', specifically when initiated by PowerShell or a process associated with 'RemotePC'. This rule aims to identify the loading or execution phase of the MassLogger RAT.
This rule detects attempts to inject malicious DLLs into common Windows processes such as svchost.exe, explorer.exe, lsass.exe, and winlogon.exe. The detection is based on the loading of DLLs with suspicious names like 'hook.dll', 'inject.dll', 'payload.dll', or 'stage.dll' by these processes, which is indicative of process injection techniques often used by malware like Remcos RAT.
Detects the execution of known adversary-in-the-middle (AiTM) phishing frameworks, such as Evilginx or Modlishka, by identifying process names, paths, or specific command-line arguments (e.g., --phishlets, --proxy, --lure) used to initiate these proxy-based phishing sessions.
Detects node.exe spawning powershell.exe as a child process, consistent with malicious npm postinstall lifecycle hooks used by the PostCSS typosquatting campaign (postcss-minify-selector-parser / postcss-minify-selector). The attack chain decrypts an AES-256-GCM blob at runtime and executes a PowerShell downloader stage.
Detects the PostCSS typosquatting campaign VBScript bootstrapper (update.vbs) using cmd.exe to extract dll.zip via tar, then launching the renamed Python executable chost.exe with loader.py to initialize the Windows RAT payload. This rule correlates two distinct process events: a wscript.exe initiated cmd.exe process executing 'tar -xf dll.zip', followed by a 'chost.exe' process executing 'loader.py' on the same device and account within a 5-minute window.
This rule detects the execution of processes with command lines containing indicators associated with 'Phantom Stealer' malware, such as 'phantom stealer', 'stealer.dll', 'phantom.exe', or 'phtantom'. This could indicate an attempt to load or execute the stealer.
This rule detects the execution of processes that contain keywords associated with Agent Tesla, RedLine, or other stealers in their command line, specifically when initiated by common Windows utilities like PowerShell, CMD, or rundll32. This pattern often indicates the loading or execution of malware.
This rule detects the use of password derivation functions (like argon2id, scrypt, pbkdf2) in command lines, which can be indicative of ransomware activity, specifically associated with Prinz Eugen. It focuses on processes like 'servertool.exe', 'encrypt.exe', and 'powershell.exe' initiating these commands.
Detects the malware presenting telephone or support instructions after blocking banking access, encouraging the victim to contact an attacker-controlled operator. This rule specifically looks for process creation events where the executable name matches common RAT naming conventions (banana, client, update, service) and the command line contains keywords related to calling support or telephone numbers, often in the context of banking or security issues.
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 a single host making Zulip REST API POST requests to multiple distinct topics, specifically looking for patterns associated with system profiling and command/tasking as observed in ZiChatBot. The rule identifies activity where a source IP uses the Zulip API to send messages to at least two different topics, with the raw request content indicating either 'channel/stream' and 'topic/subject' or keywords like 'system info', 'shellcode', 'task', or 'command'.
This rule detects a suspicious sequence of events indicative of ransomware activity, specifically the Prinz Eugen ransomware. It looks for the execution of common file compression utilities (7z.exe, rar.exe, WinRAR.exe, winzip.exe) followed by the execution of known ransomware encryption executables (servertool.exe, encrypt.exe) on the same device within a 30-minute window. This pattern suggests that an attacker is compressing files before encrypting them, a common tactic to reduce the size of data for faster encryption or exfiltration.
Detects suspected NarwhalRAT activity where a process (e.g., userscreen.exe or pythonw.exe in suspicious locations) communicates with the pCloud API to resolve a dead-drop location, followed within 60 seconds by a beacon connection to a different remote IP, characteristic of C2 communication.
Detects execution of the macOS.Gaslight Rust-based implant. The rule identifies the specific malicious binary by its SHA-256 hash and targets its behavior of using runtime dynamic symbol resolution (via dlsym) to hide API calls from static analysis.
Detects HTTP responses that utilize JavaScript Web Crypto API (subtle.importKey, subtle.decrypt) or AES-GCM encryption in conjunction with data decoding functions (atob, Uint8Array.from). This behavior is characteristic of malicious landing pages, such as those used by ErrTraffic ClickFix and EvilTokens campaigns, which encrypt payloads to evade static analysis by security tools.
Detects malicious Python or JavaScript package archives (such as those used in dependency confusion attacks) that contain obfuscated code execution logic (base64 encoded commands) within package installation hooks (setup.py), or those embedding suspicious binary executables (PE/ELF headers) within the package structure.
Detects the Montana Empire Android malware, either through a direct SHA256 hash match or through structural characteristics of the APK file (such as the presence of 'post.apk') combined with specific embedded strings commonly found in the attacker's fraudulent mobile landing pages used for social proof.
Detects behavior patterns associated with Payouts King ransomware, including direct syscall-style API calls (NtAllocateVirtualMemory, NtWriteVirtualMemory, CreateRemoteThread) from processes other than trusted system binaries, and the loading of ntdll.dll from non-standard file paths (outside System32/SysWOW64). It also includes a hash-based detection for known Payouts King malicious samples.
This rule detects potential Bluekit malware activity by identifying specific CSS filter function combinations (saturate, hue-rotate, brightness, and contrast) within HTTP header data. These functions are used by Bluekit to generate unique pixel hashes for page loads, intended to bypass screenshot-based detection. The rule also flags instances where these headers co-occur with content-length and javascript identifiers.
This rule detects network connections or DNS queries originating from an endpoint towards domains or IP addresses associated with BlueKit command-and-control (C2) infrastructure, including TLDs (pk, ws, cc, su) and onion-based addresses. This activity is indicative of potential malware communication or C2 beacons.
Detects the execution of a malicious Node.js process using a fake ESLint loader named 'vscode-eioesocxetd.js'. This malware persists by modifying the global 'require' function and setting the 'global['!']' property to ensure its presence across process restarts, typically masquerading within npm package directories.
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