Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
11,839 detections
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Detects the use of standard Linux command-line utilities (e.g., cat, curl, vi) to read or reference sensitive cloud credential files or Kubernetes service account tokens. This behavior is a common indicator of credential theft or discovery activities following initial access to a Linux host.
Detects the use of standard Linux command-line utilities (e.g., cat, curl, vi) to read or reference sensitive cloud credential files or Kubernetes service account tokens. This behavior is a common indicator of credential theft or discovery activities following initial access to a Linux host.
Detects execution of common script interpreters (mshta, powershell, cmd, wscript) from typical UI-based process launch sources (explorer, RunDlg) when the command line includes indicators of malicious activity such as hidden window flags, obfuscated content, or remote URL downloads. This pattern is characteristic of ClickFix-style social engineering attacks where users are tricked into copying and executing malicious commands.
Detects anomalous process execution and loopback network activity associated with the Model Context Protocol (MCP) 'exec_in_session' method. This pattern indicates an adversary potentially abusing the AI coding assistant's MCP server capabilities to execute arbitrary commands as a C2 channel.
Detects anomalous process execution and loopback network activity associated with the Model Context Protocol (MCP) 'exec_in_session' method. This pattern indicates an adversary potentially abusing the AI coding assistant's MCP server capabilities to execute arbitrary commands as a C2 channel.
Detects a multi-stage process execution chain involving PowerShell: first, a script-based download of remote content, followed by in-memory reflection, and finally, suspicious memory allocation or thread manipulation within the same process context. This pattern is characteristic of fileless malware execution chains designed to evade disk-based detection.
Detects the execution of known tunneling and reverse proxy tools (ngrok, cloudflared, localtunnel) commonly abused by adversaries to create outbound tunnels for C2, bypass firewalls, or exfiltrate data.
Detects the creation of suspicious scheduled tasks using the Windows schtasks.exe utility. The rule flags tasks that are configured to run as SYSTEM, include PowerShell encoded commands, or target directories commonly used for persistence such as Temp, AppData, or Public.
Detects the deletion of volume shadow copies using common Windows administrative tools such as vssadmin, wmic, and PowerShell. This activity is frequently observed during the pre-encryption stage of ransomware attacks to prevent system restoration.
Detects suspicious npm preinstall activity or node_modules execution patterns involving the execution of the Bun JavaScript runtime. This behavior is often indicative of supply chain compromise where malicious npm packages attempt to drop and run unauthorized binaries to facilitate secondary payload execution.
Detects a potential web shell deployment by identifying a web server process creating or modifying a file in common web directory locations, followed shortly (within 10 minutes) by the execution of that same file.
Detects execution of shell commands containing obfuscated patterns (such as base64 decoding, hex character sequences, or piped commands) when spawned by core Citrix NetScaler service processes (nsppe, httpd, or nsaaad). This behavior is often indicative of exploitation attempts or post-exploitation activities on network appliances.
Detects web server processes (e.g., IIS w3wp.exe, Apache, Nginx, PHP-FPM) spawning suspicious child processes such as command shells (cmd, powershell, bash, sh), network utilities (curl, wget), or interpreters (python, perl). This behavior is strongly indicative of exploitation of a public-facing web application and the subsequent execution of a webshell or post-exploitation command activity.
Detects git checkout of a bare 40-hex commit SHA or the literal FETCH_HEAD ref, executed by a recognized AI coding-agent process. Narrowed to the Plugin4Shell exploitation fingerprint (checkout of a pinned-SHA-shaped or FETCH_HEAD ref) rather than ordinary branch/tag checkouts, which these agents perform constantly during normal plugin installs.
Detects a multi-stage activity where PowerShell is used to download a ZIP file, followed by the execution of a batch script (1.bat) that subsequently launches LockScreenContentServer.exe. This behavior is indicative of a DLL side-loading chain designed to execute malicious code via legitimate processes.
Detects instances where a Microsoft IIS worker process (w3wp.exe) executes commands such as 'findstr', 'Get-Content', or 'Select-Xml' to scan configuration files (e.g., applicationHost.config, web.config) or source code files (e.g., App_Code/*.cs) for sensitive information like passwords, connection strings, or API keys. This behavior is indicative of credential harvesting by an attacker using a webshell or compromised IIS process.
Detects instances where the IIS worker process (w3wp.exe) spawns the Windows command shell (cmd.exe) to execute common reconnaissance commands such as whoami, hostname, systeminfo, and net user. This behavior is strongly indicative of post-exploitation activity following a successful web shell deployment on a web server.
Detects instances where the IIS worker process (w3wp.exe) spawns the Windows command shell (cmd.exe) to execute common reconnaissance commands such as whoami, hostname, systeminfo, and net user. This behavior is strongly indicative of post-exploitation activity following a successful web shell deployment on a web server.
Detects persistence mechanisms associated with the MATCHBOIL campaign, identifying instances where a registry run key and a scheduled task pointing to an application data (%LOCALAPPDATA%) path are created by the same process within a short window, or where known specific scheduled task names and run value names are observed.
Detects persistence mechanisms associated with the MATCHBOIL campaign, identifying instances where a registry run key and a scheduled task pointing to an application data (%LOCALAPPDATA%) path are created by the same process within a short window, or where known specific scheduled task names and run value names are observed.
Detects persistence mechanisms associated with the MATCHBOIL campaign, identifying instances where a registry run key and a scheduled task pointing to an application data (%LOCALAPPDATA%) path are created by the same process within a short window, or where known specific scheduled task names and run value names are observed.
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