Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects references to specific social media handles and identifiers associated with the MEK/NCRI (National Council of Resistance of Iran) influence campaign within email URLs, device process command lines, and miscellaneous device events. It is designed to identify potential engagement with or dissemination of influence-related content on endpoints and in email communication.
This rule monitors Azure AD Sign-in logs to identify 'impossible travel' scenarios, where a user authenticates successfully from two geographically distant locations within a time window (1 hour) that would require travel speeds exceeding a plausible threshold. This behavior is a common indicator of credential compromise or session token replay attacks.
Detects instances where identified AI agents, bots, or automated assistants perform bulk access operations on mailboxes (e.g., MailItemsAccessed, Send, deletions) or data stores (e.g., FileDownloaded, FileAccessed, SearchQueryPerformed) in Microsoft 365 environments. This monitors for potentially compromised or malicious AI service accounts abusing legitimate access to harvest sensitive data.
Detects instances of OAuth device code flow authentication from suspicious sources (e.g., unfamiliar devices, non-compliant/unmanaged devices, or unusual geographic locations) that are followed closely by an OAuth application consent event. This behavior is indicative of potential consent phishing or device code phishing attacks attempting to gain persistent access to cloud resources.
This rule monitors Office 365 file download activity, identifying users whose download volume significantly deviates from their historical baseline. It specifically looks for an unusually high number of unique files downloaded in a one-hour window, while excluding known service accounts and synchronization agents like OneDrive sync client.
Detects high-risk account modifications, such as adding MFA methods or OAuth consent grants, occurring shortly after a user sign-in. This pattern is indicative of post-AiTM session theft (e.g., NovaCookies) where an adversary uses a stolen session token to modify account settings for persistence or MFA bypass.
Detects Direct Send spearphishing impersonating internal roles (IT/Finance/Procurement) with business-themed lures targeting leadership/finance titles. Rewritten: removed a non-functional sender/recipient substring check and a broken EmailPostDeliveryEvents join that made the rule rarely fire; anchored detection to the actual Direct Send signature (null envelope + domain match) and a direct IdentityInfo join; standardized auth-failure parsing to match the other rules in this set.
Detects a high volume of outbound emails (more than 20 within a one-hour window) from a single sender containing the subject line 'Payment Transaction Failed Reminder', which is a common pattern for phishing or social engineering campaigns.
Detects anomalous sign-in behavior where a device code authentication flow is initiated from one location, but the resulting session is replayed from a different IP address in a different country within a one-hour window. This behavior is indicative of an adversary capturing an authentication token via a device code phishing or relay attack and attempting to use it from their own infrastructure to bypass conditional access policies and MFA.
Detects inbound emails masquerading as reputable advisory firms (PwC or KPMG) using lookalike sender domains, combined with wire-transfer fraud phrases in the subject line. Correlates with identity logon telemetry for the same fraudulent WhatsApp Business phone number, enabling detection across both email and authentication channels. Note: message body content is not available in the EmailEvents schema, so fraud-phrase matching is subject-only.
Detects high-volume phishing emails that utilize subjects claiming extreme discounts (e.g., 65% off) and contain links to domains ending in the .shop top-level domain (TLD). The rule correlates email subjects with URL domains and alerts when multiple recipients are targeted by the same sender/domain combination.
Detects anomalous volumes of incoming emails to support aliases that contain keywords related to customer service complaints and include URLs pointing to suspicious '.shop' domains, characteristic of 'DoppelCart' or similar fake-shop impersonation phishing campaigns.
This rule monitors DNS and email traffic for domains ending in .shop that fuzzy-match against a predefined watchlist of corporate brand names. This behavior is commonly associated with phishing campaigns, brand impersonation, or typosquatting, where attackers use similar-looking domains to lure users into revealing sensitive information or credentials.
Detects anomalous, large-scale cloning or mirroring of code repositories combined with targeted access to infrastructure-as-code configuration files (e.g., .tfvars, .tfstate) or automated exfiltration of CI/CD build artifacts. This behavior is indicative of an adversary attempting to exfiltrate proprietary source code or sensitive secrets stored within repositories.
Detects interaction with known infrastructure associated with the PREY-0058 campaign, which utilizes Adversary-in-the-Middle (AiTM) phishing lures mimicking passkey or MFA registration pages to target Microsoft 365 and other SaaS applications.
Detects incoming EXTERNAL emails containing subject lines indicative of meeting invitations or call records, which include external URLs pointing to non-standard or unverified cloud storage providers, combined with explicit remote-access/support solicitation language. Requiring the remote-access/support signal and excluding internal-to-internal mail narrows this to callback-phishing style lures rather than routine meeting correspondence.
This rule monitors for user interactions with specific domains and URLs known to be associated with suspicious or malicious activity. It aggregates data from multiple sources, including email clicks (UrlClickEvents), device network activity (DeviceNetworkEvents), device browser events (DeviceEvents), and DNS queries (DnsEvents), to identify potential exposure to these indicators of compromise.
No description available.
No description available.
This rule detects network communication, email interaction, or identity logon events related to known spoofed IC3 (Internet Crime Complaint Center) domains used in business email compromise (BEC) campaigns. The detection covers multiple telemetry sources including email URL information, device network events, and identity logon logs to identify attempts to interact with fraudulent portals.
This rule detects email-based business fraud (BEC) targeting the organization, specifically looking for executive impersonation paired with financial lure terminology and sender domain mismatches. It utilizes both a blocklist of known fraudulent sender indicators (domains and addresses) and a heuristic approach analyzing discrepancies between the envelope sender domain and the header sender domain combined with executive titles in display names and invoice-related keywords.
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