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Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential multimodal prompt injection attacks where an AI agent process ingests a file (PDF, image, etc.) from a browser or mail client and subsequently performs suspicious downstream activity, such as spawning a shell with execution primitives or making network connections to rare, non-reputable external domains. Covers T1204, T1059, T1105
This rule detects activity associated with the exploitation of PaperCut vulnerabilities. It looks for connections to known malicious IP addresses, the presence of specific credential harvesting tools, reconnaissance commands (whoami, tasklist) executed by the PaperCut application (pc-app.exe), suspicious PowerShell downloads of AnyDesk, and unauthorized access to PaperCut configuration files or log files containing known exploit strings.
This rule detects potentially malicious process execution chains where VBScript or unknown/suspicious binaries (such as ProfileQuickHost.exe) are used to launch Node.js processes, specifically targeting JavaScript files or VBScript agents. This pattern is often associated with the execution of remote access trojans (RATs) or custom malware loaders.
Detects x47.c botnet compiled outputs x47_bot.exe/x47_bot.dll or references to the x47.c_FF_v4.1 package directory
Detects potential arbitrary file download using a Microsoft Office application
Detects network connections to known SideCopy/ReverseRAT command-and-control infrastructure, including a static C2 IP address and two C2/hosting domains (matched exactly and as proper subdomains to avoid substring false positives).
Detects known Sauron Loader MSI installer/DLL samples by SHA-256 or the rnpkeys.exe/rnp.dll/tdwp.dll side-load pairing referenced together in a file
This rule detects a multi-stage attack chain where a device shows signs of credential theft (accessing browser credential stores or cookies) followed closely by a successful cloud authentication from that same user using a device identifier not previously observed in the last 30 days.
This rule detects non-browser processes that simultaneously access a web browser's 'Local State' file and the Windows DPAPI master key storage directory. This behavior is a common precursor to credential dumping, as adversaries must decrypt browser-protected secrets (passwords and cookies) using DPAPI keys stored in the user's profile.
Detects a potential post-compromise lateral movement sequence where a host, previously identified as accessing sensitive browser credential files by an unauthorized process, subsequently initiates RDP or WinRM connections to other internal hosts using an account not previously observed performing interactive logons on that source host.
Detects unauthorized access or modification attempts to common web browser credential storage files (such as 'Login Data' or 'key4.db') by processes other than standard, trusted web browsers (e.g., Chrome, Edge, Firefox). This behavior is indicative of credential harvesting, where an adversary attempts to steal saved login information from browser data stores.
This rule detects non-browser processes that simultaneously access a web browser's 'Local State' file and the Windows DPAPI master key storage directory. This behavior is a common precursor to credential dumping, as adversaries must decrypt browser-protected secrets (passwords and cookies) using DPAPI keys stored in the user's profile.
Detects unauthorized access to sensitive Chromium-based browser files such as 'Login Data' (password database) or 'Local State' (encryption keys) by processes other than standard web browsers (Chrome, Edge, Brave, Firefox). The rule also elevates risk if the access is followed by the execution of known data-handling tools like sqlite, python, or powershell, which are frequently used by information stealers to parse and exfiltrate browser-stored credentials.
Detects potential infostealer activity where an unsigned or non-system process accesses the Windows DPAPI master key store followed by access to common browser credential and cookie storage files within a 10-minute window. This behavior is indicative of malware attempting to decrypt and exfiltrate saved browser passwords and cookies.
Detects unauthorized access by a non-browser process to Chromium-based 'Cookies' SQLite database files, which are used by browsers like Chrome, Edge, and Brave. This behavior is a strong indicator of credential theft or session hijacking, as attackers target these files to extract session cookies and bypass MFA for cloud services.
Detects unauthorized access to common browser credential storage files (Login Data, Cookies, Web Data, Local State) by processes other than standard web browsers. This rule identifies potentially malicious activity by filtering for rare or unsigned binaries executing from common staging directories (Temp, Downloads) or accessing browser files shortly after the process launch, which is a common behavior pattern for info-stealer malware.
Detects attempts to enumerate or access Windows Credential Manager and vault files, often used by adversaries to extract cached credentials. The rule monitors for execution of vaultcmd.exe, invocation of keymgr.dll via rundll32.exe, and unauthorized access to credential storage paths in AppData by non-system processes.
Detects processes that access multiple categories of sensitive data (browser autofill, cryptocurrency wallets, password manager exports, or system fingerprinting files) within a short time window. This behavior is highly indicative of modular infostealers or data-collection malware conducting 'stacking access' to stage sensitive information for exfiltration.
Detects the presence of the signed but vulnerable DCRCVDrv.sys kernel driver, which is known to be abused in Bring Your Own Vulnerable Driver (BYOVD) attacks to terminate security processes via an unauthenticated PID-terminate IOCTL.
Detects instances where a process attempts to delete its own executable file image shortly after being launched. This behavior is often associated with malware attempting to minimize its forensic footprint, such as self-deleting installers or RAT (Remote Access Trojan) components that move to a different location or execute from memory.
Detects instances where the Node.js runtime process (node.exe) spawns a command shell (cmd.exe) or PowerShell (powershell.exe). This pattern is frequently used by malicious Node.js-based applications, RATs, or web shells to execute arbitrary commands on a compromised host.
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