Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential abuse of stolen OAuth session tokens, where refresh tokens are used to authenticate after a user has performed a password reset. This rule identifies accounts that continue to sign in from previously unseen devices or IP addresses within 24 hours post-password reset, a technique consistent with session persistence mechanisms used by adversary tools and platforms like EvilTokens.
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects sign-in events where Multi-Factor Authentication (MFA) was satisfied using an External Authentication Method (EAM) that asserts specific possession or inherence claims (e.g., 'hwk' - hardware key). This behavior may indicate an adversary attempting to bypass or forge MFA responses via a rogue EAM provider.
This rule monitors authentication activity within Microsoft Entra ID (formerly Azure AD) involving the Device Code flow. This flow is often abused by attackers through phishing to obtain access tokens. The rule detects and lists occurrences of authentication attempts leveraging the device code grant, facilitating the investigation of potentially malicious token acquisition or replay attacks.
This rule captures all successful login events to serve as the foundational data source for downstream correlation engines. It is designed to identify suspicious patterns such as credential reuse across disparate IP addresses, anomalous device fingerprints following MFA, or account logins shortly after phishing visits. This filter acts as a raw event provider for more complex logic that cannot be evaluated within a single-event context.
Detects successful user logins to accounts with names containing support-related terminology such as 'IT Support', 'Help Desk', or 'IT Department'. These accounts are often highly privileged or sensitive targets for credential abuse.
This rule monitors successful user sign-ins using the 'deviceCode' authentication protocol that originate from an IP address previously unseen for that specific user within the last 24 hours. The Device Code flow is commonly targeted in phishing campaigns to bypass traditional credential-based MFA, making anomalous logins using this protocol a high-signal indicator of account compromise.
Detects anomalous authentication patterns in Microsoft 365 logs where a valid session is utilized across multiple distinct devices within a short timeframe (under 5 minutes) without a corresponding multi-factor authentication (MFA) challenge. This behavior is indicative of a session token replay attack, where an adversary uses a stolen session cookie to bypass MFA and access cloud services.
This rule monitors for network connections, firewall traffic, and Entra ID authentication events involving known malicious IP addresses (the 'Wall of Shame'). The rule specifically flags interactions occurring over common VPN ports, suggesting potential unauthorized access or persistence attempts via VPN services.
Detects potential device-code phishing abuse where a successful device code authentication is followed by scripted API activity using common automation user agents within a short time window (10 minutes). This behavior is indicative of an attacker who has successfully phished a user's device code and is immediately leveraging the stolen token to interact with Microsoft Graph, Azure, or Intune services.
This rule detects a multi-stage phishing attack, often referred to as 'quishing'. It identifies incoming emails containing image (JPG, PNG) or PDF attachments that embed previously unseen URLs, correlated with a subsequent sign-in event from a mobile device by the same recipient, which is a common indicator of Adversary-in-the-Middle (AiTM) credential harvesting.
Detects MFA fatigue or push-bombing attacks where a user account experiences an abnormally high volume of MFA request denials in a short duration (10 minutes), followed by a successful authentication event. The rule specifically looks for evidence where the successful authentication potentially originates from a different IP address than the failed attempts.
Detects phishing emails containing suspicious URLs pointing to PaaS platforms (Azure Static Web Apps, Cloudflare, Firebase) that exhibit credential harvesting characteristics (branded keywords or base64 patterns). The rule correlates these emails with subsequent clicks and a successful M365 sign-in by the same user within 30 minutes of the click, indicating a probable successful credential compromise.
Detects Azure AD sign-in events using the device code authorization flow where only single-factor authentication was performed. This pattern is indicative of potential device code phishing attacks where users are tricked into entering codes on attacker-controlled pages to grant access tokens, bypassing standard MFA requirements.
Detects a sequence of suspicious activities associated with EvilTokens-style session hijacking. This includes the identification of non-interactive sign-in events involving the redemption of a refresh token without secondary MFA, followed by the creation or modification of Exchange Online mailbox rules to facilitate unauthorized email forwarding or exfiltration.
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 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.
Detects successful authentication events associated with the Azure AD Device Registration Service (resource ID 01cb2876-7ebd-4aa4-9cc9-d28bd4d359a9). This rule identifies successful registrations or sign-ins to the service, which may be leveraged by adversaries to register unauthorized devices for persistent access or to bypass conditional access policies.
Detects anomalous sign-in patterns indicative of real-time MFA relay attacks, where a user principal authenticates successfully from multiple distinct IP addresses and geographical locations within a short time window (15 minutes), suggesting the active interception of credentials and MFA challenges by a Phishing-as-a-Service platform.
Detects a suspected Multi-Factor Authentication (MFA) fatigue attack, characterized by a user denying three or more consecutive MFA authentication requests in a short period (10 minutes) followed by a successful authentication approval. This behavior often indicates an adversary bombarding a user with push notifications to eventually solicit an accidental or coerced approval.
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