Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects a multi-stage attack pattern originating from a web-based service. It identifies a web application process (like w3wp.exe, httpd.exe, or java.exe) spawning suspicious child processes (cmd.exe, powershell.exe, etc.), followed by the creation of new files and external network connections. This chain of behavior is highly indicative of web shell exploitation, post-exploitation command execution, and data exfiltration or C2 communication.
This rule detects established outbound network connections to 'devtunnels.ms', which is a legitimate service often abused by adversaries to tunnel RDP traffic and bypass network security controls or firewall restrictions. This behavior is indicative of unauthorized remote access setup.
Detects the use of ScreenConnect client processes initiating rapid outbound network connections to multiple distinct devices within a short timeframe (1 hour). This behavior is often indicative of unauthorized lateral movement, automated discovery, or mass-deployment of remote access sessions using legitimate administrative software.
Detects network traffic directed to the Telegram Bot API (api.telegram.org) characterized by TLS SNI indicators or specific HTTP URI structures (e.g., /bot). This behavior is indicative of malware or automated tools using the Telegram platform as a command-and-control (C2) channel for beaconing, command delivery, or data exfiltration.
Detects TLS connections to known CHOSEN BRICK cloud object-storage exfiltration endpoints (VultrObjects, StorjShare, Backblaze B2) and repeated Telegram Bot API document-upload calls consistent with data exfiltration. An earlier revision attempted to chain a Telegram-session flowbit to a later cloud-storage upload, but Suricata flowbits are scoped to a single flow and cannot correlate across the two separate connections involved here, so that cross-flow pair was removed as not functionally valid; each remaining rule fires independently on direct traffic to a known exfil channel.
This rule detects potential malicious activity by monitoring for known malicious file hashes (MD5) across file and process events, and correlating them with known Command and Control (C2) infrastructure communication patterns, including specific IP addresses and URI paths.
This rule detects potential malicious activity by monitoring for known malicious file hashes (MD5) across file and process events, and correlating them with known Command and Control (C2) infrastructure communication patterns, including specific IP addresses and URI paths.
This rule detects potential malicious activity by monitoring for known malicious file hashes (MD5) across file and process events, and correlating them with known Command and Control (C2) infrastructure communication patterns, including specific IP addresses and URI paths.
This rule detects potential malicious activity by monitoring for known malicious file hashes (MD5) across file and process events, and correlating them with known Command and Control (C2) infrastructure communication patterns, including specific IP addresses and URI paths.
This rule detects a correlation between host-level reconnaissance activity using WMI (via PowerShell or WMIC) to query system information, followed by network exfiltration to a known C2 IP address over a specific URI within a 10-minute window.
This rule detects a correlation between host-level reconnaissance activity using WMI (via PowerShell or WMIC) to query system information, followed by network exfiltration to a known C2 IP address over a specific URI within a 10-minute window.
This rule identifies successful network connections from local devices to a predefined list of known malicious IP addresses within the last 7 days. Such connections often indicate active communication between a compromised endpoint and adversary-controlled infrastructure.
This rule identifies successful network connections from local devices to a predefined list of known malicious IP addresses within the last 7 days. Such connections often indicate active communication between a compromised endpoint and adversary-controlled infrastructure.
Detects outbound network connections to known command-and-control IP addresses associated with the SpiceRAT malware family. The rule monitors DeviceNetworkEvents for successful connections or connection attempts over ports 80 and 443.
Detects Remote Desktop Protocol (RDP) connections established over known suspicious high ports or to specific remote IP addresses associated with known C2 operator infrastructure (SpiceRAT). This behavior indicates potential remote interactive access by an adversary.
Detects outbound network connections to known command-and-control IP addresses associated with the SpiceRAT malware family. The rule monitors DeviceNetworkEvents for successful connections or connection attempts over ports 80 and 443.
Detects Remote Desktop Protocol (RDP) connections established over known suspicious high ports or to specific remote IP addresses associated with known C2 operator infrastructure (SpiceRAT). This behavior indicates potential remote interactive access by an adversary.
Detects DNS resolutions of known SpiceRAT command-and-control hostnames to multiple distinct C2 IP addresses within a 30-day window. This behavior is consistent with automated C2 infrastructure rotation or the use of multiple redundant IP addresses for persistence.
Detects high-frequency outbound TCP connection attempts from a WSO2 API Gateway or Traffic Manager host to multiple sensitive internal management and administrative ports (22, 445, 3389, 5985, 5986). This behavior is indicative of a compromised gateway being used for lateral movement across the network.
This rule monitors for a collection of adversarial behaviors on Windows systems, including persistence mechanisms via scheduled tasks and registry run keys, tampering with security services (VSS, Windows Defender), credential harvesting attempts (LSASS memory), log and history clearing, and external network communication to known IP geolocation services.
This rule monitors endpoint telemetry (File, Process, and Network events) to identify activity associated with a pre-defined set of known malicious file hashes, IP addresses, and domains. It correlates these indicators to detect potential malware execution, persistence, or command-and-control communication on monitored devices.
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