Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 access to Firefox profile database files (cookies.sqlite, places.sqlite, permissions.sqlite) by suspicious processes that are masquerading as legitimate system maintenance or update utilities. This rule specifically targets known masquerading process names (UpdateAssistant.exe, AppUpdateHelper.exe, SysMaintenance.exe) while excluding the legitimate firefox.exe process and its installation directory.
Detects access to Firefox profile database files (cookies.sqlite, places.sqlite, permissions.sqlite) by suspicious processes that are masquerading as legitimate system maintenance or update utilities. This rule specifically targets known masquerading process names (UpdateAssistant.exe, AppUpdateHelper.exe, SysMaintenance.exe) while excluding the legitimate firefox.exe process and its installation directory.
Detects the creation, modification, or renaming of files within directories associated with GVFS (GNOME Virtual File System) or files masquerading as GVFS components. Adversaries often use these paths and file names to stage or hide malicious tools and persistence mechanisms on Linux systems.
Detects the presence of known StyleSmuggler implant binaries (noted as Rust-based implants masquerading as gvfsd-user or kworker) by matching file SHA256 hashes.
Detects the presence of the StyleSmuggler Rust-based Linux implant. The rule identifies the malicious binary by its static SHA256 hashes or a combination of indicators including masquerading as a kernel thread, utilization of gvfsd-related filenames and directories, and interaction with Redis session data.
Detects the creation, modification, or renaming of unsigned executable files (.exe, .dll, .sys, .efi) within critical Windows system directories (System32, SysWOW64, drivers, boot). The rule excludes activity triggered by known trusted OS update processes, such as TrustedInstaller or Windows Update services, and optionally flags occurrences outside defined maintenance windows.
Detects the creation, modification, or renaming of unsigned executable files (.exe, .dll, .sys, .efi) within critical Windows system directories (System32, SysWOW64, drivers, boot). The rule excludes activity triggered by known trusted OS update processes, such as TrustedInstaller or Windows Update services, and optionally flags occurrences outside defined maintenance windows.
This rule detects processes with names commonly associated with system daemons (e.g., kworker, fc-cache, chronyd, gvfsd) that are executing from non-standard, suspicious directories such as /tmp/ or user-defined hidden folders. This behavior is indicative of an adversary attempting to masquerade malicious binaries as legitimate system processes to evade detection.
Detects the execution of an executable file located within a randomly-generated, hex-like directory structure directly beneath the %AppData%\Roaming folder. This pattern is characteristic of the GoCaracal malware dropper used by the Dark Caracal threat group to evade detection by hiding executables in paths that mimic temporary or system-generated folder structures.
Detects the execution of a Faronics Deploy installer that has been renamed to mimic Adobe-related software. This technique is often used in phishing campaigns to trick users into executing binaries that lead to the silent installation of remote monitoring tools like ScreenConnect.
Detects the creation, modification, or renaming of files within directories associated with GVFS (GNOME Virtual File System) or files masquerading as GVFS components. Adversaries often use these paths and file names to stage or hide malicious tools and persistence mechanisms on Linux systems.
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 the use of the Windows 'copy /b' command to join multiple files into a single executable, specifically targeting patterns where document files are merged with a binary named 'Windowsupdate.exe'. This technique is often used to reassemble malicious payloads by combining split components or masquerading malicious content within seemingly benign file operations in temporary user directories.
Detects empty, placeholder, or abnormally long User-Agent headers often used to evade fingerprinting.
Detects instances of DLL side-loading where common application helper binaries (ClaudeDesktop.exe or JetBrains) load libcef.dll from untrusted, user-writable directories such as Downloads, Temp, or AppData. This behavior is indicative of the Claude FakeAgent campaign, which leverages side-loading for payload deployment.
Detects processes named 'kworker' (in bracket notation) that are not initiated by the legitimate 'kthreadd' parent process, which is indicative of a process masquerading as a kernel worker thread. Legitimate kworker processes are kernel threads managed by kthreadd. Processes masquerading as these can be used by malware to hide in plain sight.
Detects processes named 'kworker' (in bracket notation) that are not initiated by the legitimate 'kthreadd' parent process, which is indicative of a process masquerading as a kernel worker thread. Legitimate kworker processes are kernel threads managed by kthreadd. Processes masquerading as these can be used by malware to hide in plain sight.
Detects processes named 'kworker' (in bracket notation) that are not initiated by the legitimate 'kthreadd' parent process, which is indicative of a process masquerading as a kernel worker thread. Legitimate kworker processes are kernel threads managed by kthreadd. Processes masquerading as these can be used by malware to hide in plain sight.
Detects the creation, modification, or renaming of files within directories associated with GVFS (GNOME Virtual File System) or files masquerading as GVFS components. Adversaries often use these paths and file names to stage or hide malicious tools and persistence mechanisms on Linux systems.
Detects the presence of known StyleSmuggler implant binaries (noted as Rust-based implants masquerading as gvfsd-user or kworker) by matching file SHA256 hashes.
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