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Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects outbound HTTP/proxy connections to gouvvbo.top, the JadeProx AdaptixC2 C2 domain also hosting a credential-harvesting phishing portal that impersonates the Piar Municipality (Venezuela) tax administration system.
Detects outbound HTTP/proxy connections to gouvvbo.top, the JadeProx AdaptixC2 C2 domain also hosting a credential-harvesting phishing portal that impersonates the Piar Municipality (Venezuela) tax administration system.
This rule detects proxy requests directed to the legitimate Microsoft OAuth 2.0 device authorization endpoint (/common/oauth2/deviceauth). This activity is indicative of OAuth device code phishing, where a user is tricked into entering a malicious or attacker-provided device code into the legitimate Microsoft device login page to complete an authentication flow and grant unauthorized access to an attacker-controlled application.
During my vacation, I've been enjoying conversations with people from different countries about their national teams and the World Cup. What I don't expect (although it certainly can happen) is a Mexican speaking Japanese, a Spaniard speaking Russian, or an Egyptian speaking Spanish. Yet, this is becoming more and more common, and I love it. Our world is becoming increasingly connected and multicultural.
However, the same logic doesn't always apply to emails.
That thought inspired me to build a KQL query that I'll explore further after my break, but I wanted to share it now. The idea is detect emails where the language doesn't match the expected language(s) of the sender's country. While this isn't a detection by itself, it can be a valuable hunting signal when combined with other indicators.
KQL Query Filter options:
EmailCount < X → Filter based on the number of emails observed.
Country !in ("Spain") → Exclude countries with a higher false-positive ratio.
SenderDomains !in ("Domain1","Domain2") → Exclude trusted sender domains.
However, the same logic doesn't always apply to emails.
That thought inspired me to build a KQL query that I'll explore further after my break, but I wanted to share it now. The idea is detect emails where the language doesn't match the expected language(s) of the sender's country. While this isn't a detection by itself, it can be a valuable hunting signal when combined with other indicators.
KQL Query Filter options:
EmailCount < X → Filter based on the number of emails observed.
Country !in ("Spain") → Exclude countries with a higher false-positive ratio.
SenderDomains !in ("Domain1","Domain2") → Exclude trusted sender domains.
This rule detects proxy requests directed to the legitimate Microsoft OAuth 2.0 device authorization endpoint (/common/oauth2/deviceauth). This activity is indicative of OAuth device code phishing, where a user is tricked into entering a malicious or attacker-provided device code into the legitimate Microsoft device login page to complete an authentication flow and grant unauthorized access to an attacker-controlled application.
Detects the presence of specific configuration strings ('design' and 'flow_type') within HTTP response bodies, which are indicative of the Kali365 phishing kit decrypting its configuration at runtime via the browser. This pattern is characteristic of credential harvesting pages.
Detects web server request patterns associated with a 'Kali365' phishing campaign that utilizes device code authorization flows. The rule identifies suspicious JSON design payloads that simulate various enterprise brands (e.g., Microsoft 365, DocuSign, Adobe) in combination with a 'device_code' flow identifier, indicative of a credential or token-harvesting attack.
Detects web server request patterns associated with a 'Kali365' phishing campaign that utilizes device code authorization flows. The rule identifies suspicious JSON design payloads that simulate various enterprise brands (e.g., Microsoft 365, DocuSign, Adobe) in combination with a 'device_code' flow identifier, indicative of a credential or token-harvesting attack.
Detects the presence of specific configuration strings ('design' and 'flow_type') within HTTP response bodies, which are indicative of the Kali365 phishing kit decrypting its configuration at runtime via the browser. This pattern is characteristic of credential harvesting pages.
Detects outbound HTTP/proxy connections to gouvvbo.top, the JadeProx AdaptixC2 C2 domain also hosting a credential-harvesting phishing portal that impersonates the Piar Municipality (Venezuela) tax administration system.
Detects the presence of specific configuration strings ('design' and 'flow_type') within HTTP response bodies, which are indicative of the Kali365 phishing kit decrypting its configuration at runtime via the browser. This pattern is characteristic of credential harvesting pages.
This rule detects incoming emails with subject lines containing keywords associated with invoice, payment, or banking detail changes. These patterns are highly characteristic of Business Email Compromise (BEC) and social engineering campaigns designed to redirect financial transactions to fraudulent accounts.
Detects web server request patterns associated with a 'Kali365' phishing campaign that utilizes device code authorization flows. The rule identifies suspicious JSON design payloads that simulate various enterprise brands (e.g., Microsoft 365, DocuSign, Adobe) in combination with a 'device_code' flow identifier, indicative of a credential or token-harvesting attack.
Detects instances where a user receives an email containing a link to SharePoint or OneDrive, but upon clicking the link, the user is redirected to a different, non-Microsoft domain. This behavior is indicative of a phishing attempt using legitimate file-sharing services to bypass initial URL filtering.
This rule detects scenarios where an email containing a specific URL has been soft or hard deleted from a user's mailbox (often by security automated systems), but a user has subsequently clicked that same URL. This often indicates a race condition or a failure in security controls where a malicious link was delivered and accessed before or during the removal process.
Detects network traffic containing a characteristic 'Loading in progress...' string, which is associated with the 'Kratos' animated envelope loading screen used in fake Microsoft 365 credential harvesting pages.
This rule detects potential OAuth Device Code Flow phishing attacks where users are directed to malicious lure pages on romnor[.]ca to enter a Microsoft device code. It also alerts on authentication activity associated with a specific malicious OAuth client ID (d3590ed6-52b3-4102-aeff-aad2292ab01c) known to be used by a phishing backend to poll and claim OAuth tokens.
This rule detects network activity associated with a phishing campaign impersonating the RENAPO CURP lookup service. It monitors for TLS SNI and HTTP Host headers containing the typosquatted domain 'gobf.mx', as well as HTTP responses containing specific keywords related to the Mexican CURP registration form originating from this domain.
This rule detects potential phishing attempts by identifying emails that contain links to legitimate Microsoft Forms (forms.office.com) with lures commonly associated with document-related phishing (e.g., 'shared a document', 'invoice'). The rule then correlates this with user click activity to identify instances where the user was redirected from the Microsoft Forms site to an external, potentially malicious URL.
This rule detects access to known adversary-in-the-middle (AiTM) phishing infrastructure mimicking Microsoft login pages. It identifies malicious URLs matching specific randomized path token patterns or those hosting a known phishing domain, while also monitoring for associated session-specific parameters such as 'rt=', 'PHPSESSID', and 'preload=1' cookies, as well as traffic interacting with legitimate 'login.microsoftonline.com' domains in a proxy context.
This rule identifies suspicious email messages that contain isolated blocks of text preceded by at least two whitespace characters (including newlines, carriage returns, or tabs). This pattern is often used by threat actors to obfuscate content, attempt to bypass email gateway filters, or hide malicious strings from security scanners by breaking up content flow.
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