Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential account takeover or persistent access via MFA manipulation by correlating recent MFA-related sign-in failures with subsequent successful identity management operations such as updating security info or registering a new MFA method. This behavior pattern is frequently associated with Adversary-in-the-Middle (AiTM) phishing or vishing attacks where an attacker compromises credentials, overcomes MFA challenges, and then establishes their own MFA device to maintain persistent access.
Detects bulk SharePoint/M365 file access or download either from a known UNC6671 exfiltration IP, or via a scripting-library user agent that is new for the user and exceeds a volume threshold within a short session window.
This rule detects potentially unauthorized command-line activity originating from Power Platform-related execution environments (such as Copilot Studio or Power Platform sandboxes). It specifically monitors for the execution of common system administration binaries like cmd, powershell, or curl, which, when triggered from within a low-code/cloud runtime environment, may indicate a sandbox escape or an attempt to interact with the underlying host operating system.
Detects users who have downloaded more than 50 files from cloud storage applications within a single hour, potentially indicating data exfiltration or mass data harvesting.
Detects a user registering a new MFA or authentication method within a short window after multiple failed Entra ID sign-in attempts, without a corresponding verified helpdesk password-reset ticket. This pattern is indicative of vishing or helpdesk-impersonation attacks aimed at hijacking user accounts by circumventing MFA controls.
Detects anomalous mailbox activity in Microsoft 365 where a user account performs both search operations and mail item access, particularly when the activity originates from multiple IP addresses or exceeds a threshold of mail items accessed within a one-hour window. This behavior often indicates potential mailbox compromise or unauthorized data collection.
Detects a password reset followed by the deletion of two or more verified security-notification emails (matched to actual notification sender domains) within 24 hours, prioritizing permanent deletions as higher-confidence evidence-destruction behavior.
Detects the creation of a new inbox rule that performs email manipulation actions (forward, redirect, delete, move, or stop processing) shortly after a user account has logged in with a high or medium risk score, or an unusual result type. This pattern is commonly indicative of account compromise where an attacker establishes persistence or data exfiltration via mailbox rules.
Detects instances where a single user account performs a large volume of file downloads (50 or more unique files) within a 30-minute window from Office 365 services. This behavior may indicate unauthorized data exfiltration or mass collection of sensitive information.
Detects OAuth applications receiving permissions to the tenant, used for persistence and data theft. A consented app holds its own token and survives password resets and MFA, which is why consent phishing and post-compromise app registration are favored by both commodity BEC actors and nation-state (PerfectData is linked to Midnight Blizzard / APT29). Tiered: a hardcoded list of known-abused app IDs (PerfectData, eM Client, rclone, Supermailer, and others), layered over a scope-characteristic tier that catches bespoke apps by the permissions they request (Mail/EWS, Files/Sites, Directory, Application, offline_access), with admin/AllPrincipals consent escalating blast radius. Parses all three consent event shapes and resolves app identity across them.
This rule detects anomalous, high-volume file access activity within SharePoint by monitoring the 'FileAccessed' operation. It calculates a 14-day rolling baseline for each user and triggers an alert when the hourly 'FileAccessed' count significantly exceeds this baseline, specifically when no corresponding 'FileDownloaded' events are present. This behavior aims to detect stream-based data exfiltration techniques that bypass standard download-based DLP controls.
Detects potential password spraying activity characterized by a high number of distinct IP addresses failing authentication for a specific user, followed shortly by a successful authentication for that same user from a geographic location outside the United Kingdom.
Detects inbound voice calls that spoof corporate helpdesk numbers. The rule triggers when an incoming call from an external/PSTN trunk matches a known helpdesk number and exhibits signs of spoofing, specifically either a mismatch between the current call's carrier and historical baseline carrier for that number, or a report by the recipient that the call was suspicious.
This rule detects potentially malicious activity where an attacker, having performed a password reset or MFA change on a compromised account, attempts to hide their tracks by rapidly deleting security-related notification emails (e.g., password reset alerts) shortly after they arrive in the user's mailbox. It correlates Exchange mailbox operations with audit log account security changes to filter out routine noise.
Detects non-interactive sign-ins (refresh-token usage) for Microsoft Purview Communication Compliance reviewer accounts (Administrator, Analyst, or Investigator roles) that originate from IP addresses not observed for the user in the previous 21 days. This behavior is indicative of potential token theft or session hijacking attempting to bypass multi-factor authentication.
Detects anomalous spikes in per-user M365 (SharePoint and Exchange) activity volume by comparing current 15-minute intervals against a 30-day rolling baseline (mean + 3 standard deviations). This behavior may indicate mass data staging or exfiltration activities common in precursor phases of extortion or data theft.
This rule detects high-volume file access or download operations in SharePoint or OneDrive, performed by non-browser user agents (e.g., Python, PowerShell, cURL, Go). An elevated volume of such actions within a short timeframe is indicative of automated, scripted interaction, which may represent malicious data exfiltration, automated content scraping, or potential account compromise.
This rule detects potential mass data retrieval or excessive access to sensitive-labeled files by an individual user through Microsoft Copilot within a one-hour window. By monitoring the volume of distinct sensitivity-labeled objects accessed, it identifies behavior consistent with a user or compromised account performing high-volume information gathering.
This rule detects potential data exfiltration via email by identifying mass near-identical background-image URLs in the body of an email. The rule looks for a high volume (8+) of distinct URLs that contain short parameters (indicative of encoded or smuggled data) within a single email. It further refines the detection by checking for the presence of specific CSS-like syntax often used in CSS-injection keylogging techniques to force the browser or email client to send background-image requests.
This rule monitors web browser URL click events for specific patterns (createssopasskey, addssopasskey) often used in vishing-lure campaigns. It identifies potential Adversary-in-the-Middle (AiTM) credential harvesting attempts by cross-referencing clicked URLs against an organization's approved SSO domain allowlist and verifying the presence of an internal referrer in the redirect chain. If a user clicks a suspect link that does not originate from a known internal source and points to an unauthorized external domain, the event is flagged.
Detects a sudden spike in subscription/confirmation-themed emails to a single recipient within a 10-minute window, significantly exceeding that recipient's historical baseline, excluding properly authenticated reputable bulk senders. This pattern is consistent with 'email bombing' used by UNC6692 to overwhelm targets before follow-up vishing/Teams-based IT impersonation social engineering.
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