Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the use of pcalua.exe to launch executables or scripts located in potentially transient or user-writable directories such as Temp, Downloads, or AppData. This behavior is indicative of an adversary attempting to execute payloads while bypassing security controls or masquerading as legitimate system processes.
Detects command-line execution patterns that exhibit hallmark traits of LLM-generated code, such as overly verbose and explanatory comments, appearing alongside common obfuscation or decoding primitives (e.g., base64, iex, eval). This combination suggests the use of AI to assist in creating decoy logic or burying malicious payloads within legitimate-appearing scripts to evade detection.
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects artifacts associated with the JWR phishing framework client engine, specifically focusing on the presence of self-referential .toString().search() anti-debugging checks, decoy variable naming conventions, and WebSocket communication components (JWRCID/JWRCVV, ws-worker.js) used for session establishment.
Detects the execution of shell interpreters (PowerShell, CMD, Bash, Zsh) with suspicious command-line arguments typically associated with malicious activity, such as encoded commands, hidden window styles, or network download requests, when initiated by common user-facing applications like web browsers or Windows Explorer.
Detects malicious bash scripts identified as part of the BYOB C2 framework infrastructure. These scripts are designed to download and install second-stage payloads such as Meterpreter or XMRig-style cryptominers. The rule identifies these scripts by their specific naming conventions, embedded C2 infrastructure indicators, and persistence mechanisms including crontab, systemd, and rc.local.
Detects the creation or modification of a file within the /etc/cron.d/ directory, followed shortly by a Bash process invocation using /dev/tcp redirection. This pattern is commonly used by attackers to achieve persistence via cron and establish reverse shells, bypassing potential limitations of default system shells that do not support /dev/tcp syntax.
Detects Sauron Loader stage-2 payload execution: a randomly-named file dropped in %TEMP% and executed within 5 minutes by a native launcher (rundll32/regsvr32/msiexec/cmd/powershell/wscript). Scoped to devices that already show the confirmed rnpkeys.exe side-load from ProgramData\keyroll, turning a very noisy fleet-wide 'temp file executed by native binary' heuristic (matches countless legitimate installers/updaters) into a targeted next-stage check on hosts with corroborated Sauron Loader activity. Also fixes an unused/dead variable and an ambiguous post-join column reference.
Detects instances where the Node.js process (node.exe) is executed with a command-line argument referencing 'sharedLoad.min.js'. This is often used in web-based applications or potentially malicious obfuscated scripts, but may flag legitimate JavaScript automation tasks.
Detects execution of remote payloads by piping the output of network utilities like curl or wget directly into a shell interpreter (bash, sh, zsh). This pattern is a common technique used by attackers to execute malicious scripts directly from a remote server without saving a file to disk.
This rule detects instances where mshta.exe acts as a parent process to initiate powershell.exe. It specifically looks for command line arguments that employ obfuscation techniques, such as character casing variations (e.g., 'POWERsHeLl'), while simultaneously excluding standard casing, combined with flags typical of non-interactive execution (e.g., -NonInteractive or /w h /c). This pattern is commonly used by adversaries to bypass security controls and execute scripts hidden from user view.
Detects the deletion of a specific file named 'Evernote.zip' located within the 'C:\Users\Public\' directory when executed by Windows Script Host (wscript.exe or cscript.exe). This activity is often associated with the cleanup of second-stage archives used during malicious operations.
This rule detects a specific persistence technique used by AvisLoader malware. It monitors for the creation of a .lnk.backup file alongside a corresponding .lnk shortcut modification in common shell locations (Desktop, Taskbar, etc.), coupled with the execution of wscript.exe or cscript.exe referencing the 'VLCAssistant' VBScript within a short time window. This sequence indicates an attempt to persist malicious activity by backing up existing shortcuts and replacing them with a launcher for the AvisLoader payload.
Detects the creation of multiple suspicious scheduled tasks using schtasks.exe initiated by scripting engines (wscript.exe, cscript.exe). The rule filters for specific task names associated with known malicious patterns and XML definition files located in a specific directory path, identifying potential automated persistence or malware installation behavior.
This rule detects activities associated with the MacSync backdoor, specifically focusing on persistence mechanisms such as LaunchAgent manipulation, .repair-run scripts, and suspicious GIT hook usage. It also correlates these events with the termination of macOS notification agents (BTMNotificationAgent, NotificationCenter, BackgroundTaskManagementAgent), which is a tactic used to suppress security alerts during malicious operations.
Detects a sequence of events where a potential multimedia lure (PDF, image, or media file) is created or downloaded via a web browser or communication client, followed by an AI agent (e.g., ChatGPT, Claude) accessing the file, and subsequently initiating a shell execution process (PowerShell, CMD, etc.) involving suspicious command-line patterns or references to the original file. This behavior is indicative of an AI-assisted prompt injection attack where malicious content is processed and executed through agent tooling.
Detects a sequence of events where a potential multimedia lure (PDF, image, or media file) is created or downloaded via a web browser or communication client, followed by an AI agent (e.g., ChatGPT, Claude) accessing the file, and subsequently initiating a shell execution process (PowerShell, CMD, etc.) involving suspicious command-line patterns or references to the original file. This behavior is indicative of an AI-assisted prompt injection attack where malicious content is processed and executed through agent tooling.
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