Ibrahim Saud
@tektrixIndiaCompletionist
2 followers18,458 downloads7,120 copies47 likes38,601 views
11,679 detections
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Detects evidence of a malicious browser extension, identified by extension ID flkebkiofojicogddingbdmcmkpbplcd, designed to redirect search traffic through a typosquatted domain 'perplexity-ai.online'. The rule monitors for file-system creation of the malicious extension, modifications to browser preferences files, manipulation of system registry keys to enforce the search provider, and outbound network connections to the malicious domain from major web browsers.
Detects execution of potential BeepRAT shellcode loaders (tcc.exe or LuaJit.exe) using specific command-line arguments, as well as the creation of associated files (temp.bin, config.ini.c) or execution patterns initiated by HFY.exe.
Detects the execution of AWS STS 'get-caller-identity' commands via a network utility (curl) initiated by common development tools like VS Code, node, or amazonq-lsp. This behavior is indicative of potential cloud credential theft or reconnaissance performed through a compromised developer environment.
Detects indicators of the BeepRAT malware (associated with Operation DragonClone), including specific process execution patterns of HFY.exe, LuaJit.exe, or tcc.exe, network connections to known C2 infrastructure on port 18848, keylogger file creation, and malicious task scheduling or TCC loader execution techniques.
Detects network communication associated with BeepRAT, specifically identifying direct TCP connections to a known command-and-control IP address on a non-standard port or DNS requests directed at a specific malicious domain.
Detects BeepRAT malware activity, including network communication to its command-and-control (C2) server on port 18848 and the creation of screenshot or video artifacts by known loader processes (HFY.exe, LuaJit.exe, tcc.exe). It also monitors for unauthorized network connections to the known BeepRAT C2 IP address.
Detects instances where common development runtime processes (e.g., node, python, shells) spawn child processes whose command lines contain references to sensitive credential environment variables such as AWS access keys, GitHub tokens, or SSH authentication sockets. This behavior often indicates that a developer or an automated tool is insecurely passing credentials via command-line arguments to subprocesses.
Detects the execution of AWS CLI commands by common scripting interpreters (Node.js or Python). This behavior is often indicative of automated cloud environment reconnaissance or credential testing using compromised access keys or instances.
This rule detects activities associated with the TaskWeaver JavaScript loader and its potential second-stage payload, Djinn Stealer. It monitors for JavaScript files (like jquery.js) being executed by Windows scripting hosts (wscript.exe, cscript.exe) or Node.js, identifies suspicious child process spawning behavior (e.g., cmd.exe, powershell.exe, system reconnaissance tools) from these scripting engines, and flags outbound network connections by these processes to common web ports that may indicate command-and-control (C2) communication.
Detects the execution of LuaJit.exe with a config.ini script, which acts as a Lua-based shellcode loader for BeepRAT. The loader uses Lua FFI to call Windows APIs such as VirtualAlloc and CreateThread to execute shellcode stored in temp.bin directly in memory. This pattern is indicative of fileless execution techniques employed by the BeepRAT remote access trojan.
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