Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors for the execution of Node.js processes involving a file named 'parser.js' and a component or argument referred to as 'ldata'. This behavior is characteristic of specific application workflows, but when observed as a standalone or unusual process, it may indicate unauthorized script execution or the activity of a malicious node-based tool.
This rule detects activities related to Tampermonkey (a popular browser extension for userscripts) or interactions with paste.sh, often used for hosting scripts or payloads. The rule monitors both process-level executions and network requests for these indicators, which may be associated with malicious script execution or browser-based credential or session theft.
This rule monitors for a multi-stage attack pattern involving two potential indicators: first, it identifies phishing emails containing a 'Google Docs' link combined with an attachment named 'API Logic Flaw'. Second, it detects browser activity involving the paste of JavaScript code or suspicious browser clipboard activity, which may indicate an attacker attempting to execute malicious scripts directly in the user's browser context.
Detects Run key persistence pointing to the known VBScript staging directory (C:\Users\Public\Libraries\Default\Lib\Lib1) used by the worm-like ScreenConnect campaign (Aug 2026), matching known script filenames (WindowsServiceHost.vbs, 1.vbs-4.vbs) invoked via wscript.exe/cscript.exe.
Detects Run key persistence pointing to the known VBScript staging directory (C:\Users\Public\Libraries\Default\Lib\Lib1) used by the worm-like ScreenConnect campaign (Aug 2026), matching known script filenames (WindowsServiceHost.vbs, 1.vbs-4.vbs) invoked via wscript.exe/cscript.exe.
This rule detects the presence of specific file artifacts and directory paths associated with the 'Mini Shai-Hulud' malicious campaign, which involves the compromise of the 'openapi-react-query-codegen' npm package. It monitors for indicators of compromise (IOCs) such as specific malicious JavaScript and shell script filenames, as well as persistence artifacts like plist and service files.
This rule detects suspicious process execution originating from web server applications (e.g., php-fpm, apache2, nginx). It looks for common shell interpreters or command-line utilities (e.g., bash, curl, python) triggered by these web server processes when they contain command execution function strings in their command lines (e.g., system, shell_exec, passthru), which is a common indicator of web shell activity or post-exploitation command execution.
This rule detects potentially malicious command-line activity involving powershell.exe or mshta.exe that is initiated by a web browser process (chrome.exe, msedge.exe, firefox.exe, or iexplore.exe). It monitors for indicators such as encoded commands, usage of Invoke-Expression, download cradles, hidden window flags, and specific known IOCs, correlating these events with recent browser activity to identify potential drive-by download or browser-based exploitation attempts.
Detects the execution of Node.js processes where the command line contains the argument 'parser.js'. This is often used by adversaries to execute JavaScript-based payloads or custom scripts for malicious purposes.
Detects command-line execution (cmd.exe, powershell.exe) originating from a python.exe process tree, correlated with long-running, frequent outbound public network connections from the same python.exe process. This behavior is consistent with the SynkLoader RAT module, where a loader uses a Python process to execute system commands and maintain persistent C2 channels.
Detects suspicious command execution patterns commonly associated with ClickFix-style social engineering attacks. The rule identifies Terminal processes executing shell commands that retrieve remote content via curl, followed by base64 decoding and/or piping directly into a shell interpreter (zsh/sh/bash), which is a common technique for executing obfuscated malicious payloads.
Detects multiple methods of tampering with Windows security controls, including disabling Windows SmartScreen via registry, bulk removal of Mark-of-the-Web (Zone.Identifier) via scripting, and disabling driver signature enforcement (TestSigning/NoIntegrityChecks) using BCDedit. These actions are indicative of an adversary attempting to bypass security protections to facilitate the execution of untrusted or malicious code.
Detects multiple methods of tampering with Windows security controls, including disabling Windows SmartScreen via registry, bulk removal of Mark-of-the-Web (Zone.Identifier) via scripting, and disabling driver signature enforcement (TestSigning/NoIntegrityChecks) using BCDedit. These actions are indicative of an adversary attempting to bypass security protections to facilitate the execution of untrusted or malicious code.
Detects multiple methods of tampering with Windows security controls, including disabling Windows SmartScreen via registry, bulk removal of Mark-of-the-Web (Zone.Identifier) via scripting, and disabling driver signature enforcement (TestSigning/NoIntegrityChecks) using BCDedit. These actions are indicative of an adversary attempting to bypass security protections to facilitate the execution of untrusted or malicious code.
The following analytic detects a Python process making an outbound network connection during package installation.
Adversaries can abuse `setup.py` build scripts by leveraging `distutils`/`setuptools` command classes to execute arbitrary code, including network beacons to third-party domains, the moment a malicious Python package is installed.
This activity is significant because it allows adversaries to establish a foothold or exfiltrate data without any direct interaction from the victim beyond running `pip install`.
If confirmed malicious, this could indicate a successful software supply chain compromise.
Adversaries can abuse `setup.py` build scripts by leveraging `distutils`/`setuptools` command classes to execute arbitrary code, including network beacons to third-party domains, the moment a malicious Python package is installed.
This activity is significant because it allows adversaries to establish a foothold or exfiltrate data without any direct interaction from the victim beyond running `pip install`.
If confirmed malicious, this could indicate a successful software supply chain compromise.
Detects the execution of python.exe or pythonw.exe from locations other than standard installation directories (C:\Python, C:\Program Files\Python), accompanied by the presence of associated DLLs (msvcp150/160.dll or python3xx.dll). This behavior is often indicative of portable Python environments being used for malicious script execution.
This rule detects the execution of specific DLP-related shell scripts (dlp.sh, dlp-docker.sh) being invoked by Terraform processes. This pattern may indicate suspicious automated infrastructure configuration or an attempt to bypass security controls by leveraging IaC tools to execute scripts.
This rule detects the execution of specific DLP-related shell scripts (dlp.sh, dlp-docker.sh) being invoked by Terraform processes. This pattern may indicate suspicious automated infrastructure configuration or an attempt to bypass security controls by leveraging IaC tools to execute scripts.
This rule detects the execution of specific DLP-related shell scripts (dlp.sh, dlp-docker.sh) being invoked by Terraform processes. This pattern may indicate suspicious automated infrastructure configuration or an attempt to bypass security controls by leveraging IaC tools to execute scripts.
Detects execution of pythonw.exe (windowless Python) from user-writable directories (e.g., AppData, Temp, Downloads) when launched by common parent processes typically associated with initial access or execution, indicative of the SynkLoader C2 malware.
Detects potential ClickFix-style attacks on macOS where a user visits a suspected malicious lure page (hosted on sites.google.com) and shortly after executes a specific malicious command pattern (related to OpenAI Codex installer) in a terminal shell within 15 minutes.
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