Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a suspected account compromise sequence where an account first authenticates to a Microsoft Teams application from infrastructure associated with TeamFiltration (e.g., specific AWS ranges), followed by a rapid (within 2 minutes) authentication to a VPN or SAML service provider from a different IP address, indicative of an account pivot.
Detects a suspected account takeover pattern where an Azure AD account logs into the Azure Portal shortly after experiencing failed authentication attempts from the same IP address. The detection correlates password spraying or VPN probing activity (multiple failed logins against different users from a single IP) with subsequent successful or near-successful logins (MFA enrollment interrupts) on the Azure Portal, signaling potential post-compromise activity.
Detects a suspected account takeover pattern where an Azure AD account logs into the Azure Portal shortly after experiencing failed authentication attempts from the same IP address. The detection correlates password spraying or VPN probing activity (multiple failed logins against different users from a single IP) with subsequent successful or near-successful logins (MFA enrollment interrupts) on the Azure Portal, signaling potential post-compromise activity.
Detects a suspected account takeover pattern where an Azure AD account logs into the Azure Portal shortly after experiencing failed authentication attempts from the same IP address. The detection correlates password spraying or VPN probing activity (multiple failed logins against different users from a single IP) with subsequent successful or near-successful logins (MFA enrollment interrupts) on the Azure Portal, signaling potential post-compromise activity.
Detects a suspected account takeover pattern where an Azure AD account logs into the Azure Portal shortly after experiencing failed authentication attempts from the same IP address. The detection correlates password spraying or VPN probing activity (multiple failed logins against different users from a single IP) with subsequent successful or near-successful logins (MFA enrollment interrupts) on the Azure Portal, signaling potential post-compromise activity.
Detects the TeamFiltration/UNK_CondorFiltration spray signature: a large
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
Detects a distributed password spraying campaign targeting cloud accounts, characterized by a large number of distinct accounts being targeted simultaneously from multiple AWS-hosted IP addresses, with a low volume of attempts per account per hour to evade standard threshold-based detection.
Detects a distributed password spraying campaign targeting cloud accounts, characterized by a large number of distinct accounts being targeted simultaneously from multiple AWS-hosted IP addresses, with a low volume of attempts per account per hour to evade standard threshold-based detection.
Detects a distributed password spraying campaign targeting cloud accounts, characterized by a large number of distinct accounts being targeted simultaneously from multiple AWS-hosted IP addresses, with a low volume of attempts per account per hour to evade standard threshold-based detection.
Detects a distributed password spraying campaign targeting cloud accounts, characterized by a large number of distinct accounts being targeted simultaneously from multiple AWS-hosted IP addresses, with a low volume of attempts per account per hour to evade standard threshold-based detection.
Detects non-interactive sign-in activity using a Primary Refresh Token (PRT) occurring shortly after a risky or AiTM-flagged interactive sign-in for the same user, originating from a device that has not been previously associated with that user account.
This rule detects instances where a user grants high-risk OAuth application permissions (e.g., Mail or Files access) within 30 minutes of a risky or MFA-challenged sign-in event. This pattern is indicative of an Adversary-in-the-Middle (AiTM) attack where an attacker successfully steals a session and immediately establishes persistent access to the victim's resources via OAuth consent.
Detects modifications to domain federation settings or the addition of new identity providers in Entra ID occurring within 24 hours of a risky sign-in event by the same user account. This behavior is indicative of a persistence mechanism involving MFA bypass via federated authentication, often referred to as a 'Golden SAML' or 'Federated Identity Backdoor' technique.
This rule detects a correlation between high-risk or anomaly-flagged sign-ins and subsequent changes to B2B guest invitation or tenant collaboration policies by the same user account within a 30-minute window. This behavior is indicative of an adversary who has successfully hijacked a session (e.g., via AiTM or token replay) and is attempting to establish persistence or pivot by inviting external accounts or modifying B2B security settings.
Detects instances where a user grants OAuth consent to a non-verified application requesting high-privilege scopes related to mail access (Mail.Read, Mail.Send) and persistence (offline_access, full_access_as_app), which is a common indicator of consent phishing attacks.
Detects successful Azure AD sign-in attempts that utilize legacy or basic authentication protocols (e.g., POP, IMAP, SMTP, Exchange ActiveSync) where Conditional Access MFA enforcement was not applied. This behavior indicates a potential attempt to circumvent modern authentication security controls, often associated with AiTM-facilitated account takeover or legacy protocol abuse.
Detects high-risk sign-in events in Azure AD that exhibit indicators of token replay, impossible travel, or anomalous sessions, while simultaneously leveraging certificate-based authentication or valid Primary Refresh Tokens (PRT). This combination often indicates an adversary is using stolen session material or PRTs to establish persistent, MFA-exempt access to the environment.
Detects successful sign-in events using the OAuth 2.0 device authorization grant (device code flow). This technique is frequently abused in AiTM/consent-phishing campaigns where an adversary tricks a user into authorizing a device, effectively obtaining a fully authenticated session token. The rule identifies successful device-code authentications, which should be correlated with source IP discrepancies or unusual volume per tenant to identify malicious activity.
Detects successful Azure AD sign-in events where the session is marked as compliant or trusted by Conditional Access policies, but simultaneously flagged by Identity Protection as originating from an anonymized IP (e.g., residential proxy, VPN). This indicates an adversary has bypassed location-based Conditional Access controls, likely in the context of an Adversary-in-the-Middle (AiTM) phishing attack.
Detects the reuse of a single authenticated session or refresh token from multiple distinct IP addresses or ASN origins within a short timeframe following a successful MFA event. This pattern is indicative of session hijacking, where an adversary uses an Adversary-in-the-Middle (AiTM) toolkit (e.g., Evilginx) to capture a valid session cookie from a victim and replay it from their own infrastructure to bypass authentication.
Detects successful multi-factor authentication (MFA) events associated with risk signals categorized as 'unfamiliarFeatures' in Azure AD sign-in logs. This combination is often indicative of an adversary-in-the-middle (AiTM) attack, where the attacker has captured authentication tokens or is forcing an MFA prompt and receiving immediate approval from a new or suspicious device and network location.
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