Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential device code phishing activity by identifying users who successfully perform a device code authentication flow shortly before registering a new device in Azure AD. This pattern is indicative of an adversary tricking a user into authenticating a malicious device to the victim's account.
Detects phishing emails containing lures that direct users to the Microsoft device login portal to enter an attacker-supplied code. The rule correlates the delivery of these emails with subsequent successful device-code based authentication events, identifying potential token theft via the OAuth device code flow.
Detects inbound emails containing an '.r01' attachment (often associated with multi-part RAR archives) where both SPF and DMARC authentication checks have failed, and the email subject implies business-related themes like purchase orders or supply chain communication. This pattern is indicative of a spearphishing attempt.
Detects anomalous, high-volume file access or download activity in Microsoft SharePoint Online or OneDrive for Business originating from a 'python-httpx' user agent. This pattern often indicates automated data collection or exfiltration attempts using programmatic tools.
Detects the granting of OAuth application permissions, specifically targeting applications with names containing terms like 'ai', 'copilot', or 'chatbot'. The rule looks for high-privilege scopes such as Mail, Files, or Directory access, which are common indicators of consent phishing or the use of malicious AI-branded applications to gain persistent access to sensitive data in the M365 environment.
Detects anomalous, high-volume file access or preview activity in OneDrive or SharePoint from non-browser user agents. This pattern is indicative of potential data exfiltration where adversaries use scripted clients or APIs to mass-read or preview files, bypassing traditional download-based alerts.
Detects downstream delivery of likely AI-paraphrased mass-produced lure content by identifying bursts of near-duplicate subject lines from newly-seen domains with auth failures.
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
Detects Azure AD sign-in events where Multi-Factor Authentication (MFA) was reportedly satisfied by an External Authentication Method (EAM) claim without evidence of a traditional secondary authentication challenge. This behavior is indicative of a 'TrustSink' technique where a rogue or compromised OIDC provider injects a spoofed assertion of MFA success into the authentication token.
Detects phishing attempts leveraging SendGrid infrastructure to send emails that impersonate well-known financial brands. The detection looks for emails with authentication checks passing (SPF/DKIM/DMARC) where the sender domain is suspicious (e.g., .asia or .com not matching the brand) and the volume of such messages suggests an automated campaign.
Detects phishing emails masquerading as legitimate DocuSign remittance advice notifications. The rule identifies emails containing specific keywords related to PDF sharing or remittance advice originating from 'docusign' and featuring suspicious, alternating-case hyperlinks often used in credential phishing campaigns.
This rule detects phishing emails associated with the 'AnonyMousKIT' campaign that spoof Apple-related services ('Find My', 'Apple Support') using common adversary-controlled Gmail/iCloud addresses. The rule specifically targets institutional recipients in .gov, .edu, and .ac domains, identifying potential credential harvesting attempts despite the campaign's original consumer-focused pretext.
This rule monitors email traffic for attachments with suspicious file types (.htm, .xhtml, .svg, .zip) or specific filenames commonly used in phishing campaigns. It focuses on emails associated with Amazon SES infrastructure, often indicative of phishing attempts leveraging reputable infrastructure to deliver malicious content or stager files.
This rule detects potential Adversary-in-the-Middle (AiTM) activity by identifying a sequence where a user experiences a sign-in interruption (ResultType 50199) followed by a successful sign-in with the same SessionId but from a different, anomalous User-Agent (typically associated with automated tools like Axios). This pattern indicates the reuse of intercepted session tokens to bypass multi-factor authentication.
Detects potential token-replay persistence by identifying repeated 'MailItemsAccessed' events for the same user account from a non-native 'REST' and 'Firefox' client string, recurring at consistent ~30-minute intervals.
Detects anomalous access to email items in Microsoft 365 Exchange environments by monitoring the 'MailItemsAccessed' operation. The rule flags specific, non-standard pairings of 'ClientAppId' and 'APIId' associated with malicious activity, indicating potential unauthorized data collection or exfiltration by attackers bypassing standard Outlook client behavior.
Detects OfficeHome sign-in events featuring the 90014 error code (missing OAuth nonce). The rule looks for a specific mismatch where mobile browser User Agents are observed on a system reported as Windows 10, a pattern consistent with Adversary-in-the-Middle (AiTM) session token replay attacks attempting to access Microsoft 365 environments.
Detects anomalous Microsoft 365 session behavior where a single SessionId persists across multiple sign-ins that originate from rotating IP addresses and ASNs. The detection identifies signs of potential session token theft, specifically looking for traffic matching the Microsoft Outlook client app signature paired with non-standard user agents (e.g., Firefox or Python requests) that exhibit recurring sign-in attempts at approximately 8-hour intervals, which is typical for automated token refresh cycles.
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