Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects interaction between an internal host and the Vapi.ai API, typically used for automating AI-based voice phishing (vishing) calls. It identifies the initiation of a call via POST requests to the Vapi.ai API and subsequent callbacks from Vapi.ai to an attacker-controlled webhook endpoint used for tracking call status.
This rule set detects network communication patterns associated with the AnonyMousKIT phishing kit, specifically targeting the exfiltration of captured user credentials to the Telegram Bot API and communication with known phishing panel infrastructure. It monitors for DNS lookups of 'anomkit.shop', established TCP connections to the associated backend relay, and HTTP requests containing specific credential-related keywords directed towards the Telegram API.
This rule detects network connections (TLS SNI and HTTP requests) to domains associated with the AnonyMousKIT PhaaS (Phishing-as-a-Service) platform. It flags connections to known phishing backend domains and monitors for access to suspicious management dashboard paths commonly utilized by this threat actor for managing phishing orders and communications.
Detects network activity associated with the JWR Phishing Framework, specifically focusing on the initiation of a WebSocket upgrade request following the delivery of a checkout-themed page load containing a 'cart_data' parameter, which is characteristic of the framework's C2 communication flow.
Detects network traffic consistent with the XMRig cryptocurrency mining tool communicating with a Monero mining pool via TLS. The rule identifies specific SNI domains and direct connection attempts to known proxy IP addresses associated with cryptomining activities.
Detects network beaconing and command-and-control (C2) communication patterns associated with the RatHat Android malware family. The rule identifies registration, shell command check-ins, heartbeat signals, and task fetching activity over HTTP. It uses stateful inspection (flowbits) to correlate device registration with subsequent heartbeat behavior to improve detection fidelity.
Detects outbound HTTP GET requests directed towards FingerprintJS CDN services that are triggered from or referred by pages hosted on disposable platforms such as Vercel or Netlify. This pattern is commonly indicative of evasion gates or bot-fingerprinting lures used in phishing campaigns to profile victim environments before delivering secondary payloads.
Detects HTTP responses containing script content indicative of anti-analysis or anti-debugging techniques, such as timing checks, debugger detection, and proof-of-work challenges commonly used on adversary-in-the-middle (AiTM) phishing landing pages.
Detects DNS queries and HTTP requests associated with the OnyxC2 command and control infrastructure, including specific hardcoded domains and suspicious DNS traffic targeting newly-abused top-level domains (.top, .cyou, .lol).
Detects network activity associated with the 'VPN-for-X' browser extension, specifically targeting communication with external services used for proxy configuration fetching and dead-drop proxy list retrieval. This includes TLS SNI checks for GitHub, Blogspot, and Telegram, as well as specific URI requests for proxy configurations and server lists.
Detects network traffic to specific domains (api.hhos.ru, mainapi.store) associated with the VPN-for-X browser extension's monetization API. This behavior is indicative of command-and-control or tracking communication identified as potentially malicious within the context of a browser extension.
Detects HTTP CONNECT requests to external networks that include Proxy-Authorization headers with Basic authentication. This pattern is indicative of malicious proxy tunneling or unauthorized credential usage for bypassing security controls or establishing command and control channels via a proxy.
Detects network activity associated with the NarwhalRAT malware, specifically C2 beaconing via HTTP/DNS to known infrastructure and file downloads from staging domains.
Detects HTTP and TLS activity associated with the DSCourier malware, specifically identifying attempts to retrieve configuration files disguised as common non-executable extensions (.jpg, .txt) or utilizing non-standard network ports like 8443, which are characteristic of this threat's command and control behavior.
Detects outbound HTTP POST requests directed to 'kmot.co/board.php', which is associated with Command and Control (C2) activity from the Chinotto Python-based backdoor attributed to APT37.
Detects network activity associated with the FlowerStorm/Storm-1167 phishing campaign. The rule monitors for credential exfiltration to a specific malicious URI (e.g., /google.php) containing login parameters, as well as the delivery of spoofed Microsoft sign-in pages from the associated phishing infrastructure.
Detects network traffic (HTTP, TLS, and DNS) originating from the internal network directed toward Telegram's API endpoints (api.telegram.org) and domains (t.me). This behavior is often associated with the use of the Telegram Bot API as a command-and-control (C2) channel or for data exfiltration by malware.
Detects network traffic (HTTP, TLS, and DNS) originating from the internal network directed toward Telegram's API endpoints (api.telegram.org) and domains (t.me). This behavior is often associated with the use of the Telegram Bot API as a command-and-control (C2) channel or for data exfiltration by malware.
Detects anomalous network behavior consistent with the PolinRider malware, which uses public Ethereum JSON-RPC endpoints and blockchain explorers (e.g., Etherscan.io) as a dead-drop resolver for command-and-control (C2) communication. The rules monitor for specific RPC methods (eth_getTransactionByHash, eth_call, eth_getBalance) over HTTP/TLS and DNS resolution queries to known blockchain explorer infrastructure.
Detects network activity associated with NetSupport Manager remote access software, specifically monitoring for connections to known malicious domains and infrastructure, as well as recurring beaconing patterns indicative of command-and-control behavior.
Detects network communication to a known malicious IP address (45.32.253.166) associated with the PIVOTPIPE RAT using Cobalt Strike C2 beaconing patterns. The rule identifies TCP connections, HTTP GET requests for beacon check-ins, and HTTP POST requests for task responses.
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