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 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.
This rule detects scenarios where a user completes a device-code authentication flow, followed immediately (within 10 minutes) by the registration of an unmanaged, non-compliant device to their account. This behavior is indicative of potential token theft (e.g., EvilTokens) where an adversary uses a stolen token to register their own device as a persistent, unmanaged entity, bypassing standard corporate device enrollment controls.
This rule detects scenarios where a user completes a device-code authentication flow, followed immediately (within 10 minutes) by the registration of an unmanaged, non-compliant device to their account. This behavior is indicative of potential token theft (e.g., EvilTokens) where an adversary uses a stolen token to register their own device as a persistent, unmanaged entity, bypassing standard corporate device enrollment controls.
This rule detects scenarios where a user completes a device-code authentication flow, followed immediately (within 10 minutes) by the registration of an unmanaged, non-compliant device to their account. This behavior is indicative of potential token theft (e.g., EvilTokens) where an adversary uses a stolen token to register their own device as a persistent, unmanaged entity, bypassing standard corporate device enrollment controls.
This rule detects scenarios where a user completes a device-code authentication flow, followed immediately (within 10 minutes) by the registration of an unmanaged, non-compliant device to their account. This behavior is indicative of potential token theft (e.g., EvilTokens) where an adversary uses a stolen token to register their own device as a persistent, unmanaged entity, bypassing standard corporate device enrollment controls.
Detects anomalous post-authentication reconnaissance activities against the Microsoft Graph API, specifically the enumeration of directory objects, roles, or service principals. The rule triggers when a user account performs multi-endpoint enumeration via the Graph API within 30 minutes of a successful authentication session initiated via a device code flow that was flagged with elevated risk signals. This behavior is consistent with post-compromise reconnaissance techniques such as 'EvilTokens', where an adversary attempts to map the environment after gaining access.
Detects anomalous post-authentication reconnaissance activities against the Microsoft Graph API, specifically the enumeration of directory objects, roles, or service principals. The rule triggers when a user account performs multi-endpoint enumeration via the Graph API within 30 minutes of a successful authentication session initiated via a device code flow that was flagged with elevated risk signals. This behavior is consistent with post-compromise reconnaissance techniques such as 'EvilTokens', where an adversary attempts to map the environment after gaining access.
Detects anomalous post-authentication reconnaissance activities against the Microsoft Graph API, specifically the enumeration of directory objects, roles, or service principals. The rule triggers when a user account performs multi-endpoint enumeration via the Graph API within 30 minutes of a successful authentication session initiated via a device code flow that was flagged with elevated risk signals. This behavior is consistent with post-compromise reconnaissance techniques such as 'EvilTokens', where an adversary attempts to map the environment after gaining access.
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.
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 for OAuth device-code authentication flow completions initiated from devices flagged as non-compliant or unmanaged in Azure AD. This behavior is indicative of potential token theft via vishing or SMS-based phishing lures (consistent with Storm-3121/Storm-3032 TTPs), where an adversary tricks a user into completing a device authorization grant to facilitate MFA bypass and persistence.
This rule detects successful authentication events for any user within the monitored environment. This serves as a foundational building block for detecting anomalous user behavior, particularly when combined with additional identity provider audit logs such as MFA method usage or registration timestamps to identify potential MFA bypass or persistence via newly registered MFA devices.
Detects login events to the 'My Sign-Ins' portal (mysignins.microsoft.com) by users. This portal is a high-value target for adversaries who have gained access to a session via token theft or session hijacking, as it allows them to modify or add authentication methods (such as MFA devices) to establish long-term persistence in the victim's account.
Detects a single user account authenticating, performing Graph API reconnaissance, and conducting data exfiltration across three distinct source IP addresses within a one-hour window. This behavior is indicative of threat actors like Storm-3121 or Storm-3032 rotating infrastructure per attack stage to evade network-based detection.
Detects when a user registers a new MFA or authentication method, such as a software token or authenticator app, within one hour of a suspicious sign-in event. This pattern is commonly indicative of an adversary establishing persistence or bypassing authentication controls following account compromise via phishing or credential harvesting.
Detects a single user account authenticating, performing Graph API reconnaissance, and conducting data exfiltration across three distinct source IP addresses within a one-hour window. This behavior is indicative of threat actors like Storm-3121 or Storm-3032 rotating infrastructure per attack stage to evade network-based detection.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
Detects high-volume authentication attempts against Fortinet network appliances where multiple distinct source IPs successfully authenticate against multiple distinct accounts matching specific administrative naming patterns. This pattern is indicative of potential credential stuffing or brute-force campaigns targeting edge infrastructure.
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