Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects evidence of the MovieReaper loader technique. This behavior involves registering or rewriting Vectored Exception Handlers, allocating memory with EXECUTE_READWRITE protection, and triggering debug-break exceptions to redirect execution into raw NtProtectVirtualMemory syscalls, effectively bypassing user-mode API hooks often used for monitoring.
Detects evidence of the MovieReaper loader technique. This behavior involves registering or rewriting Vectored Exception Handlers, allocating memory with EXECUTE_READWRITE protection, and triggering debug-break exceptions to redirect execution into raw NtProtectVirtualMemory syscalls, effectively bypassing user-mode API hooks often used for monitoring.
Detects evidence of the MovieReaper loader technique. This behavior involves registering or rewriting Vectored Exception Handlers, allocating memory with EXECUTE_READWRITE protection, and triggering debug-break exceptions to redirect execution into raw NtProtectVirtualMemory syscalls, effectively bypassing user-mode API hooks often used for monitoring.
Detects execution artifacts of the MovieReaper stage 2 implant, specifically its capability to parse and load COFF modules into memory without writing them to disk. The rule monitors process command lines for 'module_init' and identifies suspicious API activity related to memory-based module loading, such as reflective DLL loading or remote thread creation.
Detects PowerShell command execution that uses bitwise XOR operations combined with the .NET [IO.File]::WriteAllBytes method. This pattern is commonly used by malware, such as AsyncRAT, to deobfuscate and drop secondary payloads or modules onto the file system during execution.
This rule detects potential persistence mechanisms where a suspicious batch file (.bat) is placed within the Windows Startup folder and subsequently executed using command-line arguments that include specific file extensions like .exe and .ini. This behavior is indicative of malware, such as remote access trojans (RATs), attempting to maintain persistence upon system reboot.
Detects the installation or presence of the GemStone browser extension backdoor. The detection logic identifies the malicious extension by flagging specific service worker file names ('background.js') located in browser extension directories, or by detecting browser extension events associated with unique indicators found in the 'AdditionalFields' metadata, specifically looking for keys such as 'kc_state', 'portal_sync_config', or a 'background.js' file reference.
Detects outbound network traffic containing cleartext Windows command shell banners, which is highly indicative of a reverse shell connection where a remote attacker has established interactive command-line access to a compromised host.
Detects post-exploitation persistence artifacts on Windows endpoints consistent with abuse of CVE-2026-18577.
Detects anomalous clipboard activity where content is repeatedly replaced by cryptocurrency wallet address patterns (Bitcoin or Ethereum) within a short timeframe. This behavior is indicative of clipboard hijacking (clipjacking), a technique used by malware like EggJagger to substitute legitimate payment addresses with attacker-controlled addresses.
This rule detects potential Server-Side Request Forgery (SSRF) activity where web application or runtime processes attempt to access the Cloud Instance Metadata Service (IMDS) or container task metadata endpoints. By monitoring network connections and application logs, the rule filters out known legitimate metadata clients and identifies suspicious processes frequently associated with web-based vulnerabilities that are repeatedly querying sensitive metadata paths.
This rule detects command line patterns associated with common Impacket tools (wmiexec, psexec, smbexec) executed via Windows processes (cmd.exe, powershell.exe) or via network connections to ports 445 and 135 initiated by Python processes. These tools are frequently used by adversaries for lateral movement, remote service execution, and command execution on compromised systems.
Detects the creation of Windows services immediately following a network logon event (Logon Type 3) using NTLM or Kerberos. The rule monitors for service names or file paths characteristic of PsExec-style remote execution tools, specifically focusing on suspicious paths (e.g., Temp, UNC paths) or file extensions (e.g., .bat, .ps1, .tmp) used by attackers to execute payloads laterally.
Detects the execution of known development, scripting, and administrative tools (e.g., Python, Node.js, GCC, Docker) from non-standard or unauthorized file paths. The rule leverages allowlists for process names, publishers, and trusted installation directories to identify potentially unauthorized usage of powerful tooling often abused by attackers for post-exploitation activities.
Detects text/report artifacts (markdown, JSON, plain text) produced by an autonomous AI-driven vulnerability research pipeline that decompiles binaries, traces cross-references, hypothesizes memory-safety flaws, and generates/debugs proof-of-concept exploits
Detects anomalous activity patterns consistent with automated firmware reverse engineering pipelines, specifically correlating the high-frequency execution of firmware analysis tools (e.g., binwalk, Ghidra) with the creation of vulnerability research knowledge base artifacts. This behavioral heuristic aims to identify potential AI-driven or automated zero-day discovery workflows by tracking tool usage density and output characteristics.
Detects artifacts of the winAgent v2.0 Windows implant line, including mod_* modules, WUEngine persistence binaries, and COM/CLSID hijack strings used by AI-assisted implant development
Detects anomalous child processes spawned by a Chrome renderer process. This behavior is often indicative of exploitation attempts, such as the BlueMoon exploit kit leveraging CVE-2026-85046, where a compromised renderer attempts to escape the sandbox or execute arbitrary code in the host process.
Detects instances where multiple executables named 'eld0.exe', 'eld1.exe', or 'eld2.exe' are executed on the same device within a short time window, all containing a 'CID=' argument in the command line. This behavior is often indicative of automated deployment, staging, or modular malware execution patterns.
Detects instances where a process attempts to directly open or access the Active Directory domain database file (NTDS.dit). Direct access to this file is a strong indicator of credential dumping attempts, as the file contains sensitive password hashes and domain information.
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.
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