Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects the execution of common security reconnaissance and enumeration tools (e.g., subfinder, nuclei, gobuster, httpx) or suspicious Python scripts typically associated with scanning and discovery activities. It uses Sysmon Process Creation events and flags instances where high-volume scanning parameters are used or where multiple distinct tools or executions are observed on a single host.
This rule detects potential exploitation of SAP Remote Function Call (RFC) mechanisms, specifically targeting abuse of SXPG_CALL_SYSTEM and SXPG_COMMAND_INSERT which allow execution of OS commands via SAP. It identifies the execution of known malicious SAP-related scripts, suspicious OS commands (such as whoami, reading /etc/passwd or /etc/shadow) spawned by SAP work processes, and command line activity originating from privileged SAP service accounts.
This rule detects suspicious activity on Oracle database hosts, including the spawning of unexpected child processes from Oracle service binaries (such as cmd.exe or shells), the creation or access of known exploit-related script filenames, and the use of UTL_FILE to write files with suspicious extensions to temporary directories, which are patterns indicative of exploitation attempts like DBMS_SCHEDULER remote code execution or data exfiltration.
Detects instances where a Node.js process spawns the 'crontab' utility, likely to modify user cron jobs. This is a common technique used by attackers to achieve persistence by scheduling periodic execution of malicious scripts or reverse shells.
Detects evidence of the MYRA RAT attempting to establish persistence via the LD_PRELOAD environment variable. This is achieved by creating or modifying malicious shared libraries (e.g., .libcache.so) and configuring system startup files (e.g., /etc/profile.d/.sh.local) to ensure the library is loaded by the dynamic linker on startup.
Detects potential keystroke logging activity using Python scripts. It monitors for Python processes invoking keylogging libraries or APIs, modification of power settings to prevent system sleep (a common tactic to maintain logger persistence), and the creation of text or log files in common user-writable directories.
Detects the execution of known forensic imaging tools (FTK Imager or AD Imager) or commands interacting with the Active Directory database (ntds.dit). This behavior is characteristic of unauthorized attempts to extract credential hashes from the NTDS.dit file for offline cracking.
Detects the creation of executable files (.exe or .dll) on a removable drive followed by the execution of a process from that same drive within a 30-second window. This behavior is indicative of an adversary using removable media to stage and execute malicious payloads.
Detects the execution of known forensic imaging tools (FTK Imager or AD Imager) or commands interacting with the Active Directory database (ntds.dit). This behavior is characteristic of unauthorized attempts to extract credential hashes from the NTDS.dit file for offline cracking.
Detects the execution of wscript.exe, msiexec.exe, or cmd.exe initiated with command lines pointing to script files (.js, .vbs) or shortcut files (.lnk) located on removable drives (d-z drive letters). This behavior is characteristic of the Raspberry Robin worm spreading via infected USB media.
Detects the execution of PowerShell or pwsh that originates from an interactive parent process like explorer.exe or cmd.exe. The rule identifies suspicious command-line patterns containing 'IEX', 'Invoke-Expression', 'Invoke-WebRequest', 'iwr', or 'IRm', while excluding encoded commands, which is indicative of potential malicious clipboard-paste activity or manual attacker intervention.
Detects Python processes binding to or establishing network connections on the local loopback interface (127.0.0.1 or ::1) on non-standard ports. This behavior may indicate a local backdoor, proxy, or C2 listener implemented in Python that is not associated with common development tools or environments.
Detects malicious node.js processes spawned from npm lifecycle hooks (e.g., install, postinstall) that exhibit suspicious command-line arguments, environment variables, or connections to known malicious domains associated with supply chain compromise campaigns.
Detects malicious npm package behavior where a postinstall lifecycle hook uses 'npm pack' or similar commands to overwrite local node_modules contents with a newer version, a technique used by packages like 'decimal-format-utils' to bypass static analysis.
Detects the installation, service creation, registry modification, and network activity associated with the Tailscale VPN tool. This rule monitors for persistent use of Tailscale, which can be utilized by threat actors to establish encrypted mesh access to internal environments.
Detects npm package installation activity or network communication originating from npm-related processes that involve identified malicious packages, maintainers, or scopes associated with supply chain attacks. Specifically monitors for the '@withgoogle' scope squatting, as well as specific malicious package names and maintainer accounts, and tracks related outbound network connections to suspicious C2 domains.
Detects execution of potentially malicious npm lifecycle scripts (preinstall/postinstall) associated with the Polymarket Trap supply chain campaign. The rule monitors node.exe spawning specific known-malicious scripts or executing shell commands via cmd.exe, often related to attacker-controlled dependency packages.
Detects instances where a Node.js process (e.g., node.exe) spawns standard system reconnaissance binaries such as whoami, hostname, systeminfo, ipconfig, or ifconfig. This behavior is indicative of malicious activity, specifically infostealer campaigns (like the Polymarket Trap / Miasma) that leverage npm postinstall scripts or other Node.js execution patterns to gather host and environment information from developer machines.
Detects the Polymarket Trap technique where a Node.js process executes 'npm pack' during a post-install phase and subsequently overwrites core module files (e.g., index.js) within the node_modules directory. This behavior is used to evade static analysis and conceal malicious code within legitimate dependency files.
Detects the creation of a Windows scheduled task using 'schtasks.exe' with the 'Highest' run level, configured to execute either 'powershell.exe' or 'wscript.exe'. This pattern is consistent with persistence mechanisms observed in Operation Poisson, where attackers establish elevated, automated execution of scripts.
Detects malicious npm dependency sideloading where a node.exe process spawns cmd.exe from a path containing 'node_modules'. This rule specifically targets the behavior observed in the Polymarket Trap / wshu.net supply chain campaign, where indirect dependencies execute malicious scripts that bypass security restrictions by launching Windows command shells at runtime.
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