Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects msiexec.exe spawning scripting or programming engines (such as PowerShell or Python) that perform LDAP directory searches and establish outbound external network connections within a specific time window.
Detects msiexec.exe spawning scripting or programming engines (such as PowerShell or Python) that perform LDAP directory searches and establish outbound external network connections within a specific time window.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects PowerShell execution involving Base64 decoding or certutil decoding combined with writing files to the AppData directory using .NET I/O methods or PowerShell cmdlets.
Detects PHP script execution interacting with the Microsoft Exchange Web Services (EWS) API, which may indicate web shell usage, email collection, or exfiltration activity.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects when the IIS worker process (w3wp.exe) spawns command-line utilities or script interpreters such as cmd.exe, powershell.exe, mshta.exe, wscript.exe, or cscript.exe. This behavior often indicates web application exploitation or webshell activity.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects the creation of cook.pth or cook.py in Python site-packages or dist-packages directories by package managers or interpreters, followed by a Python interpreter execution on the same device within one hour. This pattern matches the malicious supply chain behavior observed in compromised LiteLLM versions (e.g., 1.107.0) utilizing .pth auto-import chains for persistence and execution.
The following analytic detects the execution of the macOS osascript utility with AppleScript commands that display a dialog or alert containing potentially deceptive, credential-related, or security-themed content.
Adversaries may abuse osascript to present fake system messages or credential prompts and trick users into disclosing sensitive information.
This detection is based on command-line content and should be reviewed with the parent process, executing user, script content, and surrounding endpoint activity.
Adversaries may abuse osascript to present fake system messages or credential prompts and trick users into disclosing sensitive information.
This detection is based on command-line content and should be reviewed with the parent process, executing user, script content, and surrounding endpoint activity.
Detects an npm or pip package installation process spawning a script
interpreter or living-off-the-land binary (powershell, cmd, certutil, bitsadmin, curl,
wget, bash, sh) as a child process. CrowdStrike's 2026 Threat Hunting Report found
adversaries increasingly embed malicious setup/install scripts inside open-source packages
uploaded to npm and PyPI; these scripts execute automatically the moment the package is
written to disk during npm install / pip install, unless intercepted before execution. A
package manager process spawning a scripting engine or download utility immediately after
install is a strong indicator of an embedded malicious postinstall/setup script rather than
a normal build step.
interpreter or living-off-the-land binary (powershell, cmd, certutil, bitsadmin, curl,
wget, bash, sh) as a child process. CrowdStrike's 2026 Threat Hunting Report found
adversaries increasingly embed malicious setup/install scripts inside open-source packages
uploaded to npm and PyPI; these scripts execute automatically the moment the package is
written to disk during npm install / pip install, unless intercepted before execution. A
package manager process spawning a scripting engine or download utility immediately after
install is a strong indicator of an embedded malicious postinstall/setup script rather than
a normal build step.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects potential defense evasion activity where Windows Defender configurations are modified or disabled, followed closely within 20 minutes by a silent, quiet, or unattended software uninstallation initiated by a script interpreter or command processor on the same device.
Detects instances where package managers (pacman, makepkg, yay, paru) or their children spawn a root shell that downloads and executes external scripts via curl or wget.
Detects process creation events where common Office applications (Word, Excel, PowerPoint, Outlook) or archive/reader utilities (Acrobat, WinRAR, 7-Zip) act as the parent process to command-line interpreters, scripting engines, or administrative tools (such as cmd, powershell, wscript, cscript, mshta, rundll32, and others). This behavior is commonly associated with phishing attacks, macro execution, or exploitation of file formats leading to code execution.
The following analytic detects a process located in a potentially suspicious location making DNS queries to known URL shortening services, specifically tinyurl.
URL shorteners are frequently used by threat actors to obfuscate malicious destinations, including phishing pages, malware distribution sites, or command-and-control (C2) endpoints.
While tinyurl.com is a legitimate service, its use in enterprise environments—particularly by non-browser processes or scripts—should be considered suspicious, especially if correlated with subsequent outbound connections, file downloads, process file path or credential prompts. Analysts should investigate the source process, execution context, and destination domain to determine intent and risk.
URL shorteners are frequently used by threat actors to obfuscate malicious destinations, including phishing pages, malware distribution sites, or command-and-control (C2) endpoints.
While tinyurl.com is a legitimate service, its use in enterprise environments—particularly by non-browser processes or scripts—should be considered suspicious, especially if correlated with subsequent outbound connections, file downloads, process file path or credential prompts. Analysts should investigate the source process, execution context, and destination domain to determine intent and risk.
Detects suspicious command-line execution patterns involving Unix shells (bash, zsh, sh) spawned from terminal applications where tools like curl or wget are piped directly into a shell, base64 decoding is performed, osascript executes dialogs, or quarantine attributes are removed.
Detects the use of msxsl.exe or wmic.exe to process .xsl or .xslt files, potentially indicating the execution of embedded scripts. The rule calculates a risk score based on the combination of the utility name, the presence of an XSL/XSLT file reference in the command line, usage of suspicious file paths (e.g., Temp, AppData), and being launched by potentially suspicious parent processes like cmd.exe or powershell.exe.
Detects script-driven (curl, wget, python) outbound connections to
AI/LLM API endpoints. The campaign uses legitimate AI platform APIs as covert
command, control, and exfiltration channels, blending malicious traffic with
approved web services to evade network-based detection.
AI/LLM API endpoints. The campaign uses legitimate AI platform APIs as covert
command, control, and exfiltration channels, blending malicious traffic with
approved web services to evade network-based detection.
Detects PowerShell execution performing port checks across multiple internal hosts using Test-NetConnection in a looping construct with output redirected to a log file, indicative of post-compromise reconnaissance (such as LONEPAGE scanning).
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