Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects instances where PowerShell is used to download an executable named 'svchost.exe' from an external IP address (103.86.86.244). The rule monitors for network connections to this IP, file creation events matching specific download patterns in fonts directories, and direct command-line arguments involving the suspicious IP and file path, indicating potential malware dropper activity.
Detects the presence of the known Cyclops Blink implant by file hash (SHA256) on an endpoint, followed by a network connection to associated C2 infrastructure within one hour, aligning with typical implant beaconing or file transfer behavior.
Detects the presence of the known Cyclops Blink implant by file hash (SHA256) on an endpoint, followed by a network connection to associated C2 infrastructure within one hour, aligning with typical implant beaconing or file transfer behavior.
Detects network requests to unpkg.com or npmmirror for 'index.html' files directly under a package path. This behavior deviates from standard package management usage (which typically fetches tarballs or specific JavaScript modules) and is often associated with adversaries using npm packages as hosting infrastructure for phishing landing pages.
This rule detects network connections or DNS queries to known phishing domains (typosquatted Microsoft login domains), DeadDrop Resolver domains, and suspicious HTML payloads served from common CDN/package hosting sites (e.g., unpkg.com, npmmirror.com, cdn.jsdelivr.net, yarnpkg.com). These patterns are indicative of initial access attempts via phishing or the secondary stage of malware C2 communication.
Detects outbound HTTP traffic originating from a WordPress host containing specific signatures associated with the Mushr00w Uploader webshell, indicating command-and-control communication or data exfiltration.
Detects behavior where the ERAAgent process writes a file to disk and executes that same file shortly after (within 5 minutes). This pattern is consistent with staged payload delivery, decompression, or assembly often observed in malicious activity, specifically referencing SLEEPWALKER malware patterns.
This rule detects a suspicious sequence of events where a process with a name resembling an updater (AutoUpdate.exe or au.exe) accesses a specific remote configuration file from a herokuapp.com URL, followed by the creation or modification of specific application binaries (e.g., InstaTime.exe, ffmpegsumo.dll). This pattern is indicative of a supply chain compromise or an automated software update hijacking where malicious binaries are staged to replace legitimate application components.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
Detects suspicious file transfer and subsequent execution activity associated with the ScreenConnect (ConnectWise Control) remote access application, which may indicate exploitation of file-transfer vulnerabilities. The rule monitors for ScreenConnect processes dropping executable or script files to disk followed by the spawning of command interpreters to execute those files.
Detects a suspicious sequence of activities where PowerShell downloads or extracts specific zip files (node.zip, build.zip) to staging directories, followed by the execution of associated binaries like node.exe, winpty-agent.exe, or winpty.dll from those same locations. This behavior is indicative of an adversary staging and executing tooling within temporary user directories.
This rule detects a suspicious sequence of events where a process with a name resembling an updater (AutoUpdate.exe or au.exe) accesses a specific remote configuration file from a herokuapp.com URL, followed by the creation or modification of specific application binaries (e.g., InstaTime.exe, ffmpegsumo.dll). This pattern is indicative of a supply chain compromise or an automated software update hijacking where malicious binaries are staged to replace legitimate application components.
This is something I have seen many times during my years working in cybersecurity: users download software with a filename they recognize and trust, but the file behind that name can be something completely different.
Monitoring the filename is not enough. Monitoring the hash is better, but legitimate software changes constantly: new version, new SHA256, another hash to validate and maintain. So I started thinking about how AI agents could help us here — not by deciding what is malicious, but by doing the repetitive work for us.
For this research, I built an AI-maintained baseline of legitimate software and used it from KQL to hunt two different scenarios:
🎯 Known filename + Unknown hash + Untrusted download source
Monitoring the filename is not enough. Monitoring the hash is better, but legitimate software changes constantly: new version, new SHA256, another hash to validate and maintain. So I started thinking about how AI agents could help us here — not by deciding what is malicious, but by doing the repetitive work for us.
For this research, I built an AI-maintained baseline of legitimate software and used it from KQL to hunt two different scenarios:
🎯 Known filename + Unknown hash + Untrusted download source
Detects instances where common web server applications (e.g., Apache, Tomcat, IIS, Nginx) or Java runtime environments spawn suspicious child processes like command shells (cmd.exe, powershell.exe, sh, bash) or network utilities (wget, curl). This behavior often indicates exploitation of a web vulnerability, such as Remote Code Execution (RCE), allowing an adversary to execute commands or download further malicious payloads.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
Detects browser-based network requests to the Google Sheets Visualization API (gviz/tq) that appear to be used for fetching malicious JavaScript payloads from public Google Sheets. The rule specifically identifies instances where a process initiates these requests without any corresponding active browser session associated with standard Google Docs or Sheets editing activity.
Detects suspicious PowerShell execution spawned by common development tools or shell environments like node, npm, or WSL. The rule evaluates the process lineage and scores the command line arguments for characteristics commonly used by malicious payloads, such as hidden execution, bypass flags, network download activity, or temporary file access, which are indicative of software supply chain attacks or automated malicious script execution.
This rule detects suspicious PowerShell execution that attempts to download files from the internet using the Invoke-WebRequest cmdlet. It specifically looks for PowerShell processes launched with hidden and execution policy bypass flags, coupled with specific hardcoded malicious URL patterns associated with a known campaign (NotaFiscal/nfe_valid_access_key_2026_secure).
Detects network connections to known suspicious infrastructure, including specific domains associated with Session, catbox.moe, or targeted npm registry and GitHub API queries initiated by common command-line utilities. This behavior often suggests adversary communication, data staging, or potential tool/malware delivery.
Detects instances where Faronics Core related processes (FaronicsCore.exe, NCService.exe, ScriptRunner.exe) spawn common system utilities (curl.exe, mshta.exe, msiexec.exe) often used for downloading or executing payloads. This pattern may indicate the abuse of legitimate management software to facilitate unauthorized activity or second-stage payload delivery.
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