Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 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 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 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 high-volume, automated attempts to validate AWS credentials (access keys) from a single source IP address within a short time window. This pattern, characterized by a large number of distinct access keys being tested against identity-confirming API calls (e.g., GetCallerIdentity, AssumeRole) with a mix of success and failure, is indicative of automated credential harvesting or reconnaissance campaigns.
Detects instances where an existing, non-interactive SSO session token is reused from a suspicious network location, such as an anonymizing proxy, VPN, or VPS, or triggered by an impossible travel risk event. The rule specifically looks for token usage that lacks a fresh interactive Multi-Factor Authentication (MFA) challenge, a common indicator of session token hijacking or 'replay' attacks frequently used in cloud account takeover campaigns.
Detects a sequence of suspicious identity activities indicative of a post-account-takeover pivot. The rule identifies a user profile engaging in corporate VPN SAML SSO probing, triggering a MFA enrollment interrupt in Azure, and subsequently accessing multiple Microsoft 365 applications (Azure Portal, OfficeHome, SharePoint) within a 30-minute window.
Detects instances where a user successfully authenticates via the OAuth Device Code flow using an unmanaged or non-compliant device, followed closely by high-privileged Azure/Graph API administrative actions within a short timeframe. This behavior is indicative of a device-code phishing attack aimed at bypassing MFA controls, including FIDO2/passkeys, by compromising an active session.
Detects instances where a user successfully authenticates to a cloud service (Azure AD) from an unrecognized ASN, device, or country without performing MFA, followed shortly by high-risk actions such as mailbox rule creation, mass file downloads, or OAuth application registration. This pattern is indicative of session cookie theft or OAuth token replay used to bypass MFA.
Detects a sequence of suspicious identity activities indicative of a post-account-takeover pivot. The rule identifies a user profile engaging in corporate VPN SAML SSO probing, triggering a MFA enrollment interrupt in Azure, and subsequently accessing multiple Microsoft 365 applications (Azure Portal, OfficeHome, SharePoint) within a 30-minute window.
Detects instances where a Temporary Access Pass (TAP) is assigned to a user account, followed by a sign-in from an unmanaged or non-compliant device within one hour. This behavior is indicative of potential help-desk impersonation (vishing) attacks where an adversary obtains a TAP to bypass standard authentication controls.
Detects GitHub OAuth authorization, repository cloning, or ZIP downloads from source IP addresses that have not been observed for the specific actor within the past 30 days. This rule helps identify potential account compromise or token theft where an attacker attempts to access repository data from a new location, while specifically excluding bot/service accounts known for rotating CI infrastructure IPs.
Flags privileged or helpdesk-support account access to the identity admin console from a never-before-seen device fingerprint within minutes of a password reset on any downstream user account.
Detects instances where an administrative action involving a password reset or MFA configuration (StrongAuthenticationMethod update) is initiated by a user account that lacks the designated Helpdesk or Password Administrator role. This behavior indicates potential unauthorized privilege escalation or credential manipulation by an account not formally assigned to support workflows.
Detects an identity that performs a 'ListSecrets' operation followed by a high volume of 'GetSecretValue' or 'BatchGetSecretValue' requests within a short timeframe (15 minutes). This behavioral pattern is indicative of automated bulk exfiltration of secrets from AWS Secrets Manager, a common activity following an initial cloud environment compromise.
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