Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors network traffic for TLS SNI and HTTP URI indicators associated with known typo-squatted or spoofed Google Drive and Google Meet phishing domains. It also detects the download of a specific ZIP archive used as a phishing lure.
This rule monitors network traffic for TLS SNI and HTTP URI indicators associated with known typo-squatted or spoofed Google Drive and Google Meet phishing domains. It also detects the download of a specific ZIP archive used as a phishing lure.
This rule monitors network traffic for TLS SNI and HTTP URI indicators associated with known typo-squatted or spoofed Google Drive and Google Meet phishing domains. It also detects the download of a specific ZIP archive used as a phishing lure.
This rule monitors network traffic for TLS SNI and HTTP URI indicators associated with known typo-squatted or spoofed Google Drive and Google Meet phishing domains. It also detects the download of a specific ZIP archive used as a phishing lure.
Detects HTTP proxy traffic containing specific header or cookie patterns associated with the Evilginx2 or BigBear adversary-in-the-middle (AiTM) phishing frameworks. These frameworks use these artifacts to proxy connections and facilitate the theft of session tokens for MFA bypass.
Device code authentication flow completed, followed by subsequent session activity from a different IP/user-agent, indicating token replay to an attacker-controlled client that bypasses MFA
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
Detects inbound emails containing malicious QR codes (quishing) or HTML smuggling payloads designed to facilitate credential harvesting (AiTM). The rule identifies suspicious attachments, HTML-based obfuscation (e.g., atob, Blob) in email bodies, and QR-code-themed image attachments, filtering out internal communications.
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
Detects suspicious mobile-device HTTP traffic patterns indicative of 'quishing' (QR code phishing). The rule identifies mobile HTTP GET requests (iPhone, Android, Mobile Safari, iPad) that lack a Referer header, followed by HTTP POST requests to common credential entry URI patterns (e.g., /login, /signin) over the same protocol, which is a behavioral indicator of a user being redirected from a scanned QR code to a malicious phishing landing page.
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 web proxy requests that resemble phishing attempts targeting Apple Activation Lock. The rule identifies URLs containing specific Apple-related keywords in combination with common phishing URL paths, while filtering out legitimate Apple support documentation pages.
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 web proxy requests that resemble phishing attempts targeting Apple Activation Lock. The rule identifies URLs containing specific Apple-related keywords in combination with common phishing URL paths, while filtering out legitimate Apple support documentation pages.
Detects internal spearphishing emails containing subjects and body text commonly associated with payroll fraud, specifically attempts to solicit changes to employee direct deposit accounts by requesting voided checks or information about upcoming payments.
Detects web-proxy or webserver log activity associated with domains registered within the last 30 days that mimic branding or structure of major identity providers (Microsoft, Okta, Google, Duo). This behavior is characteristic of adversary-in-the-middle (AiTM) phishing infrastructure staging.
Detects adversary-in-the-middle (AiTM) phishing activity utilizing reverse-proxy kits (such as Evilginx2, EvilProxy, or Modlishka) to bypass MFA. The rule identifies suspicious login requests by correlating common identity provider login paths with missing security headers (CSP/HSTS) and anomalous server or hostname characteristics typical of proxied phishing infrastructure.
Detects Browser-in-the-Browser (BitB) phishing pages by inspecting web proxy or EDR-captured page content for malicious HTML/JS structures. The rule identifies fabricated browser chrome, such as fake address bars and title bars, initialized via window.open with specific dimensions, while ensuring the serving domain is not a known, legitimate identity provider.
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
This rule detects a multi-stage phishing attack, often referred to as 'quishing'. It identifies incoming emails containing image (JPG, PNG) or PDF attachments that embed previously unseen URLs, correlated with a subsequent sign-in event from a mobile device by the same recipient, which is a common indicator of Adversary-in-the-Middle (AiTM) credential harvesting.
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