Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects outbound HTTP traffic originating from a WordPress host containing specific signatures associated with the Mushr00w Uploader webshell, indicating command-and-control communication or data exfiltration.
This rule detects a suspicious sequence of events where a process with a name resembling an updater (AutoUpdate.exe or au.exe) accesses a specific remote configuration file from a herokuapp.com URL, followed by the creation or modification of specific application binaries (e.g., InstaTime.exe, ffmpegsumo.dll). This pattern is indicative of a supply chain compromise or an automated software update hijacking where malicious binaries are staged to replace legitimate application components.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
Detects network connections from common Linux system binaries (agetty, atd, polkitd, crond) to identified suspicious external domains. These binaries typically do not communicate with external internet services, suggesting potential process masquerading or compromise.
Detects processes that access sensitive browser credential or cookie files (e.g., Login Data, Cookies) followed by network activity within a 10-minute window, which is a common behavior pattern of information-stealing malware such as Amatera or ACR Stealer.
Detects outbound web requests directed at public NPM mirrors and CDNs (unpkg, npmmirror, yarnpkg, jsdelivr) that contain strings matching known malicious package names associated with the 'Beamglea/ClickFix' campaign. This activity is typically indicative of a victim visiting a deceptive Cloudflare CAPTCHA phishing page designed to execute malicious scripts in the browser.
Detects network activity from infrastructure provisioner tools (Terraform, Coder) or shell processes attempting to connect to suspicious domains (e.g., coder-infra.com) that resemble legitimate infrastructure domains. This activity is indicative of credential theft, specifically targeting OIDC tokens, SSH keys, or authentication tokens during automated provisioning processes.
Detects network connections initiated by common web browsers to a specific LinodeObjects domain or any subdomains within the linodeobjects.com infrastructure, which may indicate command and control communication or data exfiltration via legitimate cloud storage providers.
Detects network connections initiated by common web browsers to a specific LinodeObjects domain or any subdomains within the linodeobjects.com infrastructure, which may indicate command and control communication or data exfiltration via legitimate cloud storage providers.
Detects processes that access sensitive browser credential or cookie files (e.g., Login Data, Cookies) followed by network activity within a 10-minute window, which is a common behavior pattern of information-stealing malware such as Amatera or ACR Stealer.
Detects network traffic associated with the GemStone malicious browser extension, including initial registration to a command-and-control (C2) server on Cloudflare Workers, periodic heartbeat beacons, command polling, and external public IP address lookups for victim identification.
Detects network activity from infrastructure provisioner tools (Terraform, Coder) or shell processes attempting to connect to suspicious domains (e.g., coder-infra.com) that resemble legitimate infrastructure domains. This activity is indicative of credential theft, specifically targeting OIDC tokens, SSH keys, or authentication tokens during automated provisioning processes.
Detects network activity from infrastructure provisioner tools (Terraform, Coder) or shell processes attempting to connect to suspicious domains (e.g., coder-infra.com) that resemble legitimate infrastructure domains. This activity is indicative of credential theft, specifically targeting OIDC tokens, SSH keys, or authentication tokens during automated provisioning processes.
This rule detects a suspicious sequence of events where a process with a name resembling an updater (AutoUpdate.exe or au.exe) accesses a specific remote configuration file from a herokuapp.com URL, followed by the creation or modification of specific application binaries (e.g., InstaTime.exe, ffmpegsumo.dll). This pattern is indicative of a supply chain compromise or an automated software update hijacking where malicious binaries are staged to replace legitimate application components.
Detects network activity associated with the CurlRAT malware during its beaconing phase. The rule monitors for process command line arguments containing 'writeservice_info' or 'atd_get_system_info', which indicate the collection of system information, and correlates this with network connections that potentially transmit a ~10KB data payload characteristic of its check-in mechanism.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
This rule detects potential command and control (C2) activity associated with the CurlRAT malware. It monitors for both the execution of 'curl' or 'curl.exe' processes with command lines containing known C2 domains, and network traffic originating from internal devices directed toward those same domains.
Detects network activity associated with the CurlRAT malware during its beaconing phase. The rule monitors for process command line arguments containing 'writeservice_info' or 'atd_get_system_info', which indicate the collection of system information, and correlates this with network connections that potentially transmit a ~10KB data payload characteristic of its check-in mechanism.
Detects network activity associated with the CurlRAT malware during its beaconing phase. The rule monitors for process command line arguments containing 'writeservice_info' or 'atd_get_system_info', which indicate the collection of system information, and correlates this with network connections that potentially transmit a ~10KB data payload characteristic of its check-in mechanism.
Detects the specific execution pattern associated with CurlRAT, where common Linux daemons (crond, atd, agetty, polkitd) perform an outbound network connection and subsequently spawn an interactive shell (sh, bash, dash) as the root user within a 5-minute window.
Detects periodic POST requests to an external endpoint containing specific request parameters (name, value, type) and a 'User-token' header, consistent with the expected beaconing intervals of the curlRAT malware (12h or 30s fast-poll).
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