Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potentially malicious use of the device code authentication flow in Entra ID sign-in logs. The rule correlates device code usage with indicators of suspicious activity, such as rare User-Agent strings (e.g., 'python-requests') often used in phishing/relay toolkits, or sign-ins flagged by Azure AD Identity Protection as risky. It includes exclusions for known first-party Azure CLI and PowerShell clients to minimize noise from legitimate administrative activity.
Detects anomalous NTLM authentication activity (LogonType 3) where a single account or source IP attempts to authenticate to 25 or more unique hosts within a 10-minute window. This behavioral pattern is frequently observed during credential spraying, pass-the-hash attacks, or unauthorized lateral movement attempts using NTLM.
Correlates a Microsoft 365 OAuth device-code authentication event with subsequent impact actions on the same identity (device registration/PRT setup, inbox rule creation, or PRT/sign-in activity after a password reset) within a 1-hour window. Severity escalates as more distinct impact phases co-occur on the same actor, consistent with ARToken/EvilTokens post-device-code-phishing persistence chains.
Detects an authentication event using the OAuth 2.0 Device Code grant flow, immediately followed by rapid access to multiple high-value cloud resources. This pattern is characteristic of consent phishing or device code phishing, where an adversary tricks a user into authorizing a malicious application, subsequently using that application's access token to programmatically enumerate or exfiltrate data from various services.
This rule detects successful sign-in events originating from IP addresses that have previously demonstrated a password-spraying pattern (multiple failed sign-ins across distinct accounts within a two-hour window). To reduce noise, it excludes successful logins originating from 'known' Autonomous System Numbers (ASNs) where at least 10 distinct users have historically authenticated successfully. The detection further filters for sessions lacking managed device identifiers and allows for manual exclusion of specific applications, IP addresses, or geographic locations.
Detects Active Directory Federation Services (ADFS) token issuance or claims processing events (Event IDs 299, 1200-1203) that lack a corresponding preceding primary authentication audit event within the same correlation instance. This lack of correlation suggests the SAML assertion was not initiated by a legitimate login, potentially indicating the use of a forged SAML token (Golden SAML attack).
Detects successful authentication events in Azure SigninLogs that utilize the Device Code OAuth flow. Attackers may leverage this flow in phishing campaigns or to bypass MFA by tricking users into authorizing malicious devices, which can lead to subsequent token theft.
This rule detects potential brute force or password guessing attempts by monitoring Windows security logs for instances where a failed logon (Event ID 4625) is followed by a successful logon (Event ID 4624) for the same user on the same host within a 60-second window.
Detects high volumes of file download operations from OneDrive or SharePoint occurring within one hour of a device-code authentication event. This pattern is indicative of potential data exfiltration by an adversary using a stolen access token obtained via an OAuth device-code phishing attack.
This rule detects successful Azure AD sign-in events (ResultType 0) that occur following a series of repeated failed sign-in attempts (ResultType 50126) from the same user account. The activity is specifically scoped to the LSHIY IPv6 address range and utilizes Azure CLI or similar mobile/desktop client applications, which is a strong indicator of an automated password spraying or credential stuffing attack followed by a successful compromise.
Detects non-interactive sign-ins to Azure CLI using the 'python-requests' User-Agent by non-administrative users. This pattern is associated with the LSHIY password spray campaign, which exploits the OAuth ROPC flow for credential abuse against Microsoft 365.
This rule identifies successful user sign-ins originating from IP addresses known to belong to VPN services. It leverages an external list of VPN IP ranges to correlate with Azure AD SigninLogs. This can indicate an attempt to bypass geo-restrictions, hide true origin, or could be legitimate use of a VPN by an employee.
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
Detects indicators of Device Code Lab's PRT Refresh capability, where an administrator's 'Revoke all sessions' (revokeSignInSessions) action is followed by a prt-refresh backend call that reactivates the attacker's session without new user interaction, bypassing standard OAuth refresh token revocation.
Detects Microsoft Entra ID (formerly Azure AD) sign-in logs where a single user account authenticates from two different countries within a 10-minute window, which is indicative of potential account compromise or credential sharing.
Detects anomalous device code authentication sessions originating from non-corporate IP addresses using common command-line user agents, which are immediately followed by a device registration event by the same user. This pattern is indicative of OAuth device code phishing, where an attacker tricks a user into authorizing a malicious application to access their account.
Detects anomalous non-interactive OAuth token requests against Microsoft Graph that claim multi-factor authentication (MFA) satisfaction from unmanaged devices. This behavior is indicative of Adversary-in-the-Middle (AiTM) token replay attacks, where captured session tokens are reused by an attacker to bypass authentication controls, consistent with tactics used by threat actors like Storm-2755 (Payroll Pirate).
This rule computes a composite risk score for user authentication events across multiple identity and network providers (Okta, Azure AD, VPNs, etc.). It flags suspicious patterns including impossible travel, credential stuffing indicators (multiple failures followed by success), new or unknown devices, and lateral movement attempts (concurrent access to both VPN and SSO services). Only users meeting a risk score threshold of 40 or higher with at least one successful authentication are reported.
This rule detects potential session token theft or replay attacks by identifying non-interactive sign-in events that occur from a different IP or geographic location than the user's most recent successful MFA-authenticated interactive session. It flags cases where a non-interactive token is used within a short timeframe (1 hour) of an interactive session from a different location, which may indicate the exfiltration and subsequent use of session cookies or OAuth tokens.
Detects Microsoft 365 sign-in patterns indicative of an adversary bypassing Conditional Access device compliance requirements using an edge appliance proxy. The rule identifies successful authentication sessions from non-compliant or unmanaged devices that satisfy Conditional Access, often involving impossible travel or multiple source IPs, suggesting the use of an intermediary infrastructure to masquerade as a trusted location.
This rule detects potential Golden Ticket attacks by looking for multiple successful Kerberos authentication events (EventID 4624) with LogonType 3 (network logon) and a specific TicketEncryptionType (0x17), originating from the same IP address and targeting the same user, within a short timeframe and with a long ticket lifetime. A Golden Ticket attack involves an adversary forging Kerberos Ticket Granting Tickets (TGTs) to gain unauthorized access to resources.
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