Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a suspicious sequence of events indicating account takeover: a password reset, followed by an MFA factor re-enrollment, and concluding with a successful login from a geographically impossible location compared to recent history. This pattern often signifies a help-desk-assisted account compromise or token theft.
This rule monitors for the creation or modification of inbox rules in Microsoft 365 that contain financial-related keywords (e.g., 'payment', 'wire', 'invoice') and disruptive actions such as deleting, moving, forwarding, or redirecting messages. These patterns are characteristic of Business Email Compromise (BEC) attacks, where adversaries attempt to conceal financial correspondence from the victim to facilitate fraudulent transactions.
This rule detects potentially malicious Microsoft Graph API activity, such as the enumeration of directory roles, groups, applications, or service principals. It identifies patterns indicative of token theft or unauthorized access by flagging scripted clients (non-browser agents) or accounts showing anomalous behavior (multiple IPs/agents) performing rapid or repetitive enumeration queries.
Detects instances where Microsoft 365 Copilot surfaces content labeled with sensitivity markings to a user who only has access to that content via inherited or broad sharing permissions (e.g., Company link, Anonymous link, or inherited permissions), rather than explicit access. This identifies potential AI-retrieval exploitation patterns where Copilot inadvertently exposes sensitive information due to oversharing configurations.
This rule detects high-risk administrative operations in Azure Active Directory (such as role assignment, password resets, and account status changes) that occur within 3 hours of a user's sign-in. This pattern often indicates an account compromise followed by immediate privilege escalation or persistence establishment.
Detects the creation of email mailbox or transport rules that perform actions like hiding, deleting, marking as read, forwarding, or redirecting emails with finance or payment-related keywords. This behavior is indicative of a Business Email Compromise (BEC) post-exploitation workflow where adversaries attempt to conceal malicious activity or divert financial communications.
Detects instances where the device code authentication protocol is utilized. This protocol is commonly used for headless devices, but is also frequently abused by adversaries for phishing and device code flow abuse to acquire unauthorized access tokens.
This rule detects a suspicious monetization pattern where a user account experiences a high-risk sign-in event, followed shortly (within 2 hours) by the creation or modification of inbox rules. This pattern is often indicative of account compromise, where an adversary configures mailbox rules (e.g., forwarding or redirection) to facilitate data exfiltration or financial fraud.
This rule detects a suspicious monetization pattern where a user account experiences a high-risk sign-in event, followed shortly (within 2 hours) by the creation or modification of inbox rules. This pattern is often indicative of account compromise, where an adversary configures mailbox rules (e.g., forwarding or redirection) to facilitate data exfiltration or financial fraud.
This rule detects a suspicious monetization pattern where a user account experiences a high-risk sign-in event, followed shortly (within 2 hours) by the creation or modification of inbox rules. This pattern is often indicative of account compromise, where an adversary configures mailbox rules (e.g., forwarding or redirection) to facilitate data exfiltration or financial fraud.
Detects the granting of highly privileged OAuth or API scopes to AI-related applications (such as Copilot plugins, browser-automation agents, or AI connectors) immediately followed by high-volume data access activities (file reads or email transfers) performed by the same user account. This behavior is indicative of an attacker weaponizing a compromised identity to grant an external AI agent broad access to sensitive data for exfiltration or automated reconnaissance.
Detects a suspicious sequence of events where a user engagement (voice/video call) involving themes of urgency or helpdesk interaction is closely followed by a high-risk administrative action (e.g., password reset, MFA device enrollment, or financial transfer) by the same user, where the communication session context differs from standard activity, indicative of a deepfake-enabled vishing attack.
Detects anomalous account recovery or MFA reset activity performed by a single help-desk user account. A high volume of reset actions across numerous distinct users within a short duration is a key behavioral indicator of potential help-desk account compromise or insider abuse involving unauthorized account takeovers.
Detects a suspicious sequence where an account undergoes a help-desk-initiated password or credential reset, followed shortly (within 30 minutes) by the registration of a new multi-factor authentication (MFA) device for that same account. This pattern is characteristic of social engineering attacks, such as those used by UNC3944/Scattered Spider, where an adversary impersonates a user to gain initial access and subsequently establishes persistence by adding an MFA device they control.
Detects a pattern of MFA fatigue or 'push-bombing' where a user receives 5 or more MFA challenge requests within 10 minutes, immediately followed by a successful authentication event. This pattern is characteristic of attackers who have obtained user credentials and are attempting to bypass MFA by repeatedly triggering push notifications until the user grants access.
Detects a suspicious sequence of administrative actions where a user's phishing-resistant multi-factor authentication (MFA) factor, such as FIDO2, passkeys, or certificates, is removed and immediately replaced by a weaker authentication method like SMS, voice call, or TOTP. This behavior, when performed by an administrator account on a different user account, is a common indicator of an MFA bypass attempt often associated with social engineering or insider threat scenarios.
Detects high-privilege OAuth application consent grants occurring shortly after a user identity recovery event (e.g., password or MFA reset). This pattern is indicative of a help-desk social engineering attack where an adversary uses an identity reset to gain access to an account and subsequently establishes persistent access via a malicious OAuth application.
Detects high-risk identity modifications (password or MFA resets) following an IT helpdesk ticket that lacks mandatory security controls, such as callback verification, manager approval, or established ticket history. This behavior is indicative of vishing and social engineering attacks aimed at helpdesk personnel to compromise user accounts.
Detects anomalous large-volume file download or export activity from cloud repositories (SharePoint, OneDrive, or Salesforce) occurring shortly after a help-desk-mediated credential or MFA reset for the same user. This behavior is indicative of account takeover, specifically vishing-to-exfiltration patterns used by threat actors.
Detects anomalous Agentforce session activity where a user, via the General CRM subagent, queries Lead records followed shortly by an access request to Account records. This pattern is indicative of a potentially hijacked agent session attempting to pivot from lead review into unauthorized data access of broader customer information.
Detects anomalous Agentforce session activity where a user, via the General CRM subagent, queries Lead records followed shortly by an access request to Account records. This pattern is indicative of a potentially hijacked agent session attempting to pivot from lead review into unauthorized data access of broader customer information.
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