Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects network traffic originating from the RatHat Android malware, specifically identifying the 'SCROLL_DOWN' command in HTTP response bodies. This suggests the malware is receiving instructions from a C2 server to perform UI automation or interaction tasks.
This rule detects malformed SCTP packets that trigger a protocol decoding error ('pkt_too_small'). This behavior is associated with the 'DiagSpill' vulnerability (CVE-2026-74469), where specially crafted chunk sequences in the SCTP stream can cause a remote service crash or potential instability. The rule includes a threshold to mitigate noise from non-malicious malformed packets.
Detects potential misuse of the WinGet configuration feature, where remote Desired State Configuration (DSC) YAML files are retrieved using masqueraded file extensions (e.g., .jpg or .txt) or suspicious outbound connections on port 8443, which may indicate an adversary attempting to hide malicious configurations or bypass network filtering.
This rule monitors outbound network traffic for the inclusion of a Windows-style hostname pattern (e.g., 'DESKTOP-XXXXXX'), which is often used by stealer malware or RATs to identify victim machines during C2 communication. It explicitly excludes Microsoft licensing traffic to reduce false positives.
Detects a specifically malformed IPv6 Routing Header (type 0) with a 'segments_left' value of 255 preceding an Authentication Header (AH). This signature targets an exploit pattern known as 'DirtyAH6', which aims to trigger a remote kernel crash or potential remote code execution on vulnerable systems by manipulating IPv6 header processing.
This rule detects internal hosts initiating outbound SSH connections to known public tunneling services (e.g., pinggy.io). Attackers frequently use these services to bypass network firewalls and create persistent reverse SSH tunnels for remote command-and-control access. The detection logic focuses on the identification of SSH protocol traffic headers combined with specific domain targeting or repetitive connection behavior.
Detects outbound network activity associated with the ChainScript malware family, including WebSocket C2 communication identified by a specific 'X-Agent-Token' header and TLS connections to known rotating command-and-control domains.
Detects outbound network traffic (TLS and HTTP) destined for the Telegram Bot API (api.telegram.org). This pattern is often used by malicious actors for Command and Control (C2) communication, bot notifications, or data exfiltration, leveraging the legitimate Telegram infrastructure to hide malicious activity.
Detects the initialization sequence of the ORAX command-and-control framework, characterized by a handoff via a spoofed Cloudflare verification page followed by a WebSocket upgrade request.
This rule detects an HTTP GET request for 'static/js/main.js', a specific URI path associated with the JWR phishing framework's client-side engine. This indicates an interaction with a phishing infrastructure hosting malicious redirection or credential harvesting scripts.
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.
Detects network activity associated with the JWR Phishing-as-a-Service (PhaaS) platform. This includes the retrieval of the client-side JavaScript engine (main.js) from lookalike domains related to courier or government services, and subsequent client-side detection of the 'window.__HOST_MODE' flag, which indicates the browser has been primed for a specific phishing scenario.
These rules detect behavioral patterns associated with GhostCode-style anti-analysis, including URI-based gate redirection (turnstile checks), automated client filtering (User-Agent scanning), and UI-based spoofing (tab title masquerading) often used to protect malicious infrastructure from automated analysis tools and bots.
Detects HTTP GET requests to a specific path structure /scanna/ which includes a token-like identifier and a check=1 parameter. This pattern is indicative of a bot-filtering relay mechanism often used by malicious scripts or malware to validate or redirect traffic while attempting to evade security scanners.
Detects network activity associated with the 'RatHat' Android malware, specifically identifying attempts to retrieve tunnel configuration, deployment confirmation, and the initial reverse tunnel handshake using the fatedier/frp (Fast Reverse Proxy) tool.
This rule detects network activity associated with the NovaCookies Adversary-in-the-Middle (AiTM) phishing framework, specifically looking for traffic to domains with a .vu TLD, matching a specific URI pattern used for phishing lures in HTTP requests/responses, and related DNS queries.
This rule detects anomalous OAuth authorization requests to Microsoft and Google services where the 'redirect_uri' parameter points to suspicious external domains (specifically ending in .vu) or, in the case of silent Microsoft OAuth requests, points to domains outside of recognized Microsoft/Office 365 infrastructure. Such abuse is often indicative of OAuth consent phishing campaigns designed to steal application access tokens.
Detects network activity associated with Mirage2FA Adversary-in-the-Middle (AiTM) phishing infrastructure. The rules monitor for HTTP responses containing specific spoofed Microsoft 365 sign-in page content, DNS resolutions for known proxy-associated domain suffixes, and client requests fetching malicious loader scripts from suspected AiTM hosting infrastructure.
Detects network traffic associated with Mirage2FA Phishing-as-a-Service (PhaaS), including HTTP requests to specific URI patterns characteristic of their backend loader and DNS queries to known malicious domain families (cheecker.store and volatilesour.store), as well as direct TCP connections to identified hosting infrastructure.
This rule detects potential Adversary-in-the-Middle (AiTM) phishing kit exfiltration behavior. It correlates the initial victim geolocation lookup via 'api.ipgeolocation.io' with subsequent data exfiltration to the Telegram Bot API ('api.telegram.org') originating from the same host, indicating an automated sequence where victim context is gathered and then exfiltrated by the phishing kit.
This rule detects a two-stage network redirect sequence indicative of an Adversary-in-the-Middle (AiTM) phishing campaign. The first stage identifies traffic interacting with a Google Ads click-tracker, and the second stage identifies a subsequent request to an AWS S3 bucket, often used to host malicious landing pages or phishing proxies.
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