Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors DeviceNetworkEvents for any outbound network connections initiated from Windows devices to the domain 'files.surveillance-online.com', which is associated with malicious activity.
This rule detects network connections and DNS queries directed towards specific malicious domains or domains matching a pattern hosted on pages.dev, a service frequently abused for hosting malicious infrastructure such as phishing pages or command-and-control beacons.
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.
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 set detects multi-stage network patterns indicative of AiTM phishing campaigns. It identifies common redirection techniques, including lookalike domains hosting Microsoft OAuth authorize URLs, DNS resolution of Google ad-tech infrastructure followed by novel domains, malicious use of Google Meet and Google Ads click-tracking endpoints as phishing hops, and references to AWS S3-hosted intermediate landing pages.
Detects network traffic (DNS, TLS SNI, and HTTP Host headers) attempting to communicate with infrastructure associated with the EvilTokens Phishing-as-a-Service (PhaaS) platform. This activity is indicative of credential harvesting or adversary-in-the-middle (AiTM) attacks.
Detects network traffic (DNS, TLS SNI, and HTTP Host headers) attempting to communicate with infrastructure associated with the EvilTokens Phishing-as-a-Service (PhaaS) platform. This activity is indicative of credential harvesting or adversary-in-the-middle (AiTM) attacks.
Detects network activity associated with the KREMLIN browser extension communicating with a known command and control domain (luizestrelhashapr.online). The rule monitors DNS queries, TLS SNI connections, and HTTP WebSocket upgrade requests to identify potential C2 communication.
This rule hunts for indicators associated with the TrustSink technique, which involves using rogue External Authentication Methods (EAM) or malicious OIDC providers to bypass authentication or maintain persistence within a cloud environment. It monitors Azure AD sign-in and audit logs, alongside DNS and network events, for references to known malicious domains and URLs used for EAM-based attacks.
Detects browser-based network requests to 'script.google.com'. This can indicate usage of Google Apps Scripts, which are sometimes abused by attackers for Command and Control (C2) infrastructure, data exfiltration, or as a proxy for malicious payloads, by blending in with legitimate Google traffic.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
This rule detects activities associated with the AMOS (Atomic macOS Stealer) malware family by monitoring for known malicious file hashes on endpoints and network communication with domains linked to its command-and-control infrastructure.
This rule detects activities associated with the AMOS (Atomic macOS Stealer) malware family by monitoring for known malicious file hashes on endpoints and network communication with domains linked to its command-and-control infrastructure.
This rule monitors DNS query logs for connections to common public tunneling and proxy services (such as Cloudflare Tunnel, Ngrok, and others) originating from internal private IP address spaces. These services are frequently abused by adversaries to create unauthorized external access channels (reverse tunnels) into a private network, facilitating command and control or data exfiltration while bypassing firewall restrictions.
Detects network activity associated with the 'ClickFix' campaign, specifically targeting the cdnsuicaches[.]com domain. The rules identify the initial DNS query, the subsequent TLS SNI connection, and the retrieval of malicious JavaScript containing the 'cookie-captcha-complete' overlay signature. This behavior is indicative of a browser-based social engineering attack.
Sweeps Defender Advanced Hunting telemetry for known Sauron Loader indicators: 5 malicious SHA256 hashes (MSI installer, rnp.dll loader, tdwp.dll decrypter, embedded RSA private/public key blobs) across file/process/image-load events, plus 4 C2 domains and their full URLs across network and DNS telemetry. No IP indicators were published in the source reporting (C2 is domain-based over HTTPS) — the IP bucket is intentionally omitted rather than filled with placeholder data.
This rule monitors for known malicious file hashes, IP addresses, C2 domains, and specific URL markers associated with identified threat activity. It consolidates multiple detection vectors including file activity, process execution, network connections, and DNS queries to identify compromised devices communicating with attacker-controlled infrastructure.
This rule monitors for known malicious file hashes, IP addresses, C2 domains, and specific URL markers associated with identified threat activity. It consolidates multiple detection vectors including file activity, process execution, network connections, and DNS queries to identify compromised devices communicating with attacker-controlled infrastructure.
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