Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
254 detections
Filters
Last updated
All Time
Detection languages
167
41
16
14
10
Contributors
61
60
42
18
13
Categories
20,443
11,831
5,872
5,155
4,866
Platforms
133
108
85
38
34
Products / Services
112
83
65
30
30
MITRE Techniques
75
74
36
36
35
CVEs
7
6
6
6
6
Detects instances where a user account that has been flagged as risky (e.g., unfamiliar features, impossible travel, or malicious IP activity) performs a modification or registration of multi-factor authentication (MFA) security information within a short timeframe (30 minutes). This behavior is highly indicative of an adversary attempting to establish persistence or bypass authentication controls after a credential compromise.
This rule correlates endpoint-based alerts related to credential theft or infostealer malware with subsequent successful cloud identity authentication events. It identifies situations where a user, who has recently triggered a credential theft alert on an endpoint, logs into a cloud environment from a country or IP address that has not been historically associated with that user within a 24-hour window.
Detects successful Azure AD sign-in events that are flagged with a medium or high risk level and identified as anomalous by Azure AD Identity Protection. The specific combination of successful authentication alongside risk details like unfamiliar features, anonymized IP addresses, or malicious IP addresses is highly indicative of potential cloud account takeover, potentially following session token theft or infostealer activity.
Detects a sequence of events where a user performs a risky or anomalous login to Azure AD, such as from an anonymous network or an non-compliant device, followed shortly after by the registration of a new MFA method or security information. This behavior is indicative of an attacker who has compromised credentials and is attempting to establish persistence or bypass authentication controls by enrolling their own MFA device.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects a suspicious sequence of events where a user exhibits signs of account compromise—either through impossible travel patterns or the use of OAuth tokens on a new device—followed within one hour by the modification of mailbox settings, such as creating new inbox rules or modifying mailbox permissions, which is a common indicator of persistence and email exfiltration.
Detects MFA-fatigue style attacks (push-bombing) against Microsoft 365 accounts. The rule identifies a pattern where a user experiences a high frequency of MFA challenges or denials (at least 5 within a 10-minute window) immediately followed by a successful sign-in from a previously unseen IP and device, excluding phishing-resistant authentication methods and break-glass accounts.
Detects MFA-fatigue style attacks (push-bombing) against Microsoft 365 accounts. The rule identifies a pattern where a user experiences a high frequency of MFA challenges or denials (at least 5 within a 10-minute window) immediately followed by a successful sign-in from a previously unseen IP and device, excluding phishing-resistant authentication methods and break-glass accounts.
Detects potential passkey phishing follow-on activity by monitoring for successful sign-ins from unmanaged or non-compliant devices to OfficeHome or via device code flow, followed within 30 minutes by access to self-service account-management applications, accompanied by specific authentication errors (50074 or 50140).
This rule detects large-scale, non-interactive password-spraying campaigns targeting Microsoft Entra ID (Azure AD) accounts. It specifically identifies anomalous login behavior originating from Azure CLI or similar non-interactive clients, where a single source IP attempts to authenticate against a large number of distinct user accounts with a low number of failures per user within a short timeframe, characteristic of 'low-and-slow' password spraying.
Detects the reuse of a session or refresh token within a short timeframe (<= 900 seconds) where the source IP location, device identifier, or User-Agent string has materially changed. This behavior is indicative of Adversary-in-the-Middle (AiTM) attacks, where a session cookie has been stolen and replayed from an attacker's infrastructure to hijack a legitimate user's session.
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 mass influx of OAuth consent grant events for a single application from multiple users within a one-hour window. This behavior is indicative of a consent phishing campaign, where attackers lure users into granting excessive permissions to a malicious application to steal access tokens.
Detects the reactivation of a Microsoft Entra ID (Azure AD) service principal that has been inactive for 90 or more days, specifically flagging those that perform privileged Graph API operations after their return. This rule helps identify potentially compromised or stale service principals being leveraged by adversaries for persistent access.
Detects the reactivation of a Microsoft Entra ID (Azure AD) service principal that has been inactive for 90 or more days, specifically flagging those that perform privileged Graph API operations after their return. This rule helps identify potentially compromised or stale service principals being leveraged by adversaries for persistent access.
Detects a potential Primary Refresh Token (PRT) or device code phishing attack by identifying a two-step authentication sequence: first, a successful user sign-in via device code flow, followed shortly by a subsequent sign-in from a different, unmanaged, or untrusted device. This behavioral pattern often indicates an adversary using stolen device code session data to authenticate a new device session.
Detects successful sign-in events in Entra ID where MFA is marked as satisfied, but no interactive MFA challenge (e.g., Push, FIDO2, SMS) was recorded as completed in the authentication details. This behavior, when correlated with a new IP, device, or user-agent relative to a 30-day baseline, is highly indicative of session token replay or AitM (Adversary-in-the-Middle) attacks attempting to bypass MFA requirements.
Detects instances where a user account that has been flagged as risky (e.g., unfamiliar features, impossible travel, or malicious IP activity) performs a modification or registration of multi-factor authentication (MFA) security information within a short timeframe (30 minutes). This behavior is highly indicative of an adversary attempting to establish persistence or bypass authentication controls after a credential compromise.
Detects high-volume file download activity in Office 365/SharePoint/OneDrive audit logs. The rule correlates download spikes with users who have recently triggered security alerts related to session hijacking, token theft, or risky sign-ins, which are indicators of a potential cloud account takeover scenario.
Detects anomalous, high-velocity authentication activity where a single identity accesses multiple high-value SaaS applications (such as CRM, DevOps, or admin consoles) in a short time frame, correlated with risk signals indicative of token reuse or 'pass-the-cookie' attacks.
Detects anomalous authentication patterns where a user account accesses a large number of distinct SaaS/SSO resources within a short time frame from devices or IP addresses not previously associated with the user's historical baseline. This behavior is indicative of a stolen session cookie being replayed by an adversary to perform rapid lateral movement across the victim's cloud footprint.
Page 3 of 13