Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of programs directly from the root of a removable or virtual drive (e.g., ISO, IMG, VHD) via explorer.exe. This activity is a hallmark of phishing attacks that leverage container mounting to bypass Mark-of-the-Web (MOTW) security protections, as files extracted from or executed within mounted containers often fail to inherit MOTW metadata.
Detects the use of forfiles.exe to execute command-line interpreters such as cmd.exe or powershell.exe. This pattern is commonly used by adversaries as a LOLBAS (Living Off the Land Binary and Script) technique to achieve indirect command execution and bypass security controls.
Detects the loading or service registration of known vulnerable or malicious signed drivers commonly used in Bring Your Own Vulnerable Driver (BYOVD) attacks. These drivers are leveraged by adversaries to gain kernel-level privileges, bypass security controls, and terminate endpoint protection agents.
Detects a chained sequence of suspicious activity initiated by agentic AI development tools (e.g., Claude Code, Aider, AutoGen). The rule identifies the execution of these tools followed by local reconnaissance commands, lateral movement attempts, and outbound network connections originating from the same host, indicating potential automated exploitation or credential abuse.
This rule detects potentially suspicious activity involving conhost.exe, a process typically associated with console applications. It identifies conhost.exe instances running from suspicious paths (e.g., Temp, Downloads, AppData) or launched by unexpected parent processes. Additionally, it detects scenarios where conhost.exe acts as the parent process to common command-line or scripting utilities, which is an atypical behavior often indicative of an attempt to obscure malicious command execution.
Detects a chained sequence of suspicious activity initiated by agentic AI development tools (e.g., Claude Code, Aider, AutoGen). The rule identifies the execution of these tools followed by local reconnaissance commands, lateral movement attempts, and outbound network connections originating from the same host, indicating potential automated exploitation or credential abuse.
Detects rapid, multi-category reconnaissance activity initiated by AI-agent binaries (e.g., Claude, Cursor, ChatGPT). The rule identifies sessions that perform four or more distinct discovery operations—spanning account, network service, system information, and network configuration discovery—within a short time window, indicating potentially malicious autonomous exploration by an AI agent. Covers T1046, T1087, T1083, T1016
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
Detects anomalous behavioral patterns where an AI agent process (e.g., Claude Code, Cursor, Aider) performs multi-category discovery of its own runtime environment, plugins, and host configuration. The rule identifies agents that trigger processes spanning at least three distinct discovery categories (Network, File/Plugin, Software, or System) within a short timeframe, indicating potential reconnaissance of agent-authorized capabilities and tools rather than standard host exploration. Covers T1082, T1518, T1083, T1016
Detects anomalous behavioral patterns where an AI agent process (e.g., Claude Code, Cursor, Aider) performs multi-category discovery of its own runtime environment, plugins, and host configuration. The rule identifies agents that trigger processes spanning at least three distinct discovery categories (Network, File/Plugin, Software, or System) within a short timeframe, indicating potential reconnaissance of agent-authorized capabilities and tools rather than standard host exploration. Covers T1082, T1518, T1083, T1016
Detects the execution of known remote access tools (AnyDesk, TeamViewer, Quick Assist) on Windows systems. The rule is intended to be used in a correlated detection pipeline that identifies a multi-stage attack chain involving an initial email-bombing flood followed by an external Microsoft Teams vishing call impersonating IT support.
This rule detects the execution of the AnyDesk remote access tool shortly after its likely download via Microsoft Edge. This pattern is commonly associated with social engineering vishing attacks where an adversary directs a user to download and run remote access software.
Detects a multi-stage, automated attack chain performed by AI-based development agents (e.g., Claude, Copilot, Cursor). The rule correlates process discovery, credential access, file collection (staging), and exfiltration over web services within a tight 15-minute window, identifying potential autonomous exploitation and data exfiltration. Covered T1046, T1552.001, T1078, T1005, T1567
This rule detects the execution of common Node.js package managers (npm, yarn, pnpm) attempting to install specific dependencies that match known patterns of malicious or typosquatted packages often used in supply chain attacks. The detection focuses on suspicious package names that mimic common data structure library naming conventions.
Detects the creation of a Volume Shadow Copy followed by an attempt to access or copy sensitive files, specifically the NTDS.dit database or the SYSTEM registry hive, from that shadow copy. This behavior is indicative of an attempt to perform offline credential theft.
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.
This rule detects scenarios where an AI agent executes shell commands or system-level tools immediately after receiving a prompt injection attack from an untrusted source. It correlates agent audit logs—specifically identifying tool calls flagged for prompt injection—with actual endpoint process creation events. It flags process execution as 'High' severity if the command line matches common malicious patterns like encoded commands, IEX, or attempts to access credential material (e.g., lsass, mimikatz).
Detects unauthorized processes, excluding standard web browsers, accessing sensitive browser files such as Login Data, Cookies, Web Data, and Local State. This activity is indicative of credential harvesting malware attempting to steal authentication cookies, saved passwords, or browser profiles.
Detects the creation of a new local account that is immediately followed by (or associated with) execution from a process identified as an AI development or agent-based tool (e.g., Cursor, GitHub Copilot, Ollama). The rule correlates process creation events with Windows Security Event ID 4720 (User account created) and optionally checks for subsequent addition to the local Administrators group. This logic aims to surface potential unauthorized credential creation triggered by automated AI coding assistants or LLM-driven workflows.
Detects unauthorized processes attempting to access the memory of the Local Security Authority Subsystem Service (LSASS) with high-privilege access masks, a technique commonly used for credential dumping to harvest passwords and authentication tokens.
Detects the use of WinRAR to open or extract password-protected ZIP archives containing 'Setup_File' in the filename, immediately followed by the execution of a file extracted into a WinRAR temporary directory. This behavior is associated with the OnyxC2 delivery chain, where attackers use password-protected archives to bypass security scanning.
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