Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects activity consistent with the Grandoreiro banking trojan, including DLL sideloading, screen capturing, keystroke hooking, unauthorized network connections to known banking infrastructure, and suspicious data exfiltration bursts.
Detects HTTP traffic involving redirect chains from known Gmail URL shorteners (goo.gl, g.co, short.gy) that terminate at the identified credential-harvesting domain chongdaotang.net. This behavior is indicative of a phishing campaign designed to harvest user credentials through a multi-stage redirect.
Detects anomalous network traffic patterns characteristic of the Grandoreiro banking trojan, which tunnels Command and Control (C2) communications over STUN/WebRTC (UDP port 3478). The rule identifies processes that are not known web browsers or conferencing applications initiating these STUN connections, a technique used by the malware to blend with legitimate collaboration traffic.
This rule detects potential command and control (C2) beaconing activity associated with Mythic implants. It monitors for high-frequency outbound connections (20 or more) from a single device to the same external IP address within a 30-minute window across common C2 listener ports (80, 443, 8080, 8443, 7443).
This rule detects when the node.exe process initiates an outbound network connection to a specific set of non-standard, often high-numbered ports (8443, 8445, 8453, 5555, 56001-56003) over the public internet. This behavior is often indicative of potential command and control (C2) communication, reverse shells, or malicious scripts executing within a Node.js runtime environment.
This rule detects indicators of compromise associated with the TinyRCT malware, including the loading of a malicious AppDomainManager DLL by chrome_setup.exe, network connections to a known TinyRCT staging server, and the dropping of second-stage payloads such as PerfWatson2.exe to the local application data directory.
Detects the execution of the fscan network scanner binary, its use with common scanning arguments, or any network communication with the known staging IP address associated with the fscan deployment.
Detects instances where the Excel process (excel.exe) initiates outbound network connections to non-private IP addresses on specific ports often associated with command and control or data exfiltration. This rule specifically excludes known Microsoft-owned CDN and update infrastructure, aiming to identify potential exploitation activity, such as that potentially associated with CVE-2025-60727.
Detects Python processes that combine potentially dangerous pickle deserialization (pickle.loads) with network-fetching libraries (urllib, requests, socket) and decoding methods (b64decode, fromhex). This pattern is consistent with backdoors or remote access tools (RATs) that fetch encoded payloads over the network and execute them directly in memory via deserialization.
Detects download, execution, and network activity associated with the 'isp.sh' dropper script. This includes the use of common utilities like curl or wget to fetch the script from a specific C2 IP address (83.142.209.214), piping the script directly to a shell, and signs of secondary payload execution such as 'lambsys'.
This rule detects network connections or DNS queries to known public tunneling services (e.g., Cloudflare Tunnel, localtunnel, bore, devtunnels) made by processes other than common web browsers. Attackers frequently use these services to bypass firewalls and establish unauthorized reverse shells or persistent C2 channels.
Detects potential lateral movement activity where PowerShell or the Windows Remote Management (WinRM) host process (wsmprovhost.exe) initiates network connections to multiple distinct destination IP addresses over the WinRM default ports (5985/5986). This behavior is characteristic of an adversary using legitimate remote administration tools to pivot or spread across a network.
Correlates a user passing a CAPTCHA gate (Cloudflare Turnstile, reCAPTCHA) with an immediate subsequent connection to an unknown, low-prevalence domain hosting the actual phishing landing page.
Detects network communication to well-known public DNS resolvers (1.1.1.1, 8.8.8.8, 9.9.9.9) or DNS queries for their domains, initiated by processes other than standard web browsers. This behavior is often associated with non-browser applications, potential C2 channels, or hidden network activity bypassing system DNS configurations.
This rule detects potential Business Email Compromise (BEC) attempts by identifying emails containing financial keywords sent to sensitive finance/accounting roles from domains that have not been observed in the last 180 days. It then correlates this email event with subsequent device-level network activity involving banking or financial URLs initiated by the recipient user, which may indicate follow-up reconnaissance or unauthorized access.
Detects network connections from non-browser processes executing from the ProgramData directory to known dead-drop resolver forums (digitalpoint.com, letsdiskuss.com) used by Lorem Ipsum for C2 resolution. This rule specifically targets the Rapid Brigantine threat.
Detects native Windows command and scripting interpreters (e.g., cmd.exe, powershell.exe, mshta.exe) initiating external network connections to multiple distinct IP addresses, which is often an indicator of automated C2 beaconing or lateral movement activity.
This rule monitors for three categories of potentially suspicious network behavior: connections to common CDN providers over non-standard ports, high-volume HTTPS connections directly to IP addresses (IP-direct) bypassing standard domain resolution, and high-volume traffic to CDN infrastructure that may indicate domain fronting or C2 communication. Such patterns are often used by adversaries to mask egress traffic or exfiltrate data.
This rule detects pre-payload beaconing activity associated with the Meow RAT malware. It covers both network-based detection (outbound HTTP POST to known C2 domains and paths) and endpoint-based detection. Endpoint detection includes 'curl' processes communicating with known C2 infrastructure, 'osascript' processes spawned in the context of 'curl' C2 communication, and 'curl' commands using specific flags ('-k', '-s') along with a known build hash. This activity typically occurs before the main destructive payload is delivered.
This rule correlates multiple suspicious activities indicative of ransomware or destructive attacks. It detects a combination of volume shadow copy deletion, bulk file modifications, creation of suspicious scheduled tasks, and network connections occurring during periods of high file write activity. The rule triggers when multiple signals are observed or when specific high-fidelity destructive indicators are present.
This rule detects potentially malicious behavior associated with web browser processes, including the execution of Python scripts, the loading of browser extensions from non-standard directories like AppData or Temp, the creation of Python scripts by browsers in temp folders, and outbound network connections by Python processes following browser activity. These patterns are often associated with browser-based exploitation, extension-based malware, or initial access stages where a browser is used as a conduit for malicious code execution.
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