Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects instances where a user performs an interactive login followed by a non-interactive login within a 1-hour window, where the source IP address and geographical location of both sessions differ. This behavior is indicative of potential session hijacking or token theft where an attacker is using stolen session artifacts from a different location.
Detects instances where a user performs an interactive login followed by a non-interactive login within a 1-hour window, where the source IP address and geographical location of both sessions differ. This behavior is indicative of potential session hijacking or token theft where an attacker is using stolen session artifacts from a different location.
Detects instances where a user performs an interactive login followed by a non-interactive login within a 1-hour window, where the source IP address and geographical location of both sessions differ. This behavior is indicative of potential session hijacking or token theft where an attacker is using stolen session artifacts from a different location.
This rule detects modifications to Group Policy Objects (GPO) or Microsoft Entra (formerly Azure AD) policies that weaken established security controls. For GPO, it monitors Event ID 5136 for changes to security-relevant attributes (e.g., disabling firewall or real-time monitoring) in Active Directory. For Entra, it monitors audit logs for administrative operations that reduce security posture, such as disabling MFA, lowering authentication trust, or deleting Conditional Access policies. It includes filters to exclude legitimate, documented change management activities.
This rule detects modifications to Group Policy Objects (GPO) or Microsoft Entra (formerly Azure AD) policies that weaken established security controls. For GPO, it monitors Event ID 5136 for changes to security-relevant attributes (e.g., disabling firewall or real-time monitoring) in Active Directory. For Entra, it monitors audit logs for administrative operations that reduce security posture, such as disabling MFA, lowering authentication trust, or deleting Conditional Access policies. It includes filters to exclude legitimate, documented change management activities.
Detects a privilege escalation technique where an attacker with application management permissions adds a credential to the 'Office 365 Exchange Online' service principal (SP). The attacker then leverages the SP's 'Domain.ReadWrite.All' permission to add or modify a federated domain, allowing them to forge tokens for any hybrid user.
This rule detects activity associated with known indicators of compromise (IOCs) related to European political targeting campaigns. It monitors network, email, and authentication logs for connections to specific malicious domains (including .onion addresses) and IP addresses. The rule spans multiple data sources, including device network events, Entra ID sign-in logs, cloud application events, and email communications.
Detects a suspicious sequence of events where a user's password is changed or reset by an administrator (or help-desk role) followed within a short time window by that same user registering a new MFA device, potentially indicating a vishing-based account takeover attack (e.g., PREY-0058/UNC6671).
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
Detects inbound emails masquerading as reputable advisory firms (PwC or KPMG) using lookalike sender domains, combined with wire-transfer fraud phrases in the subject line. Correlates with identity logon telemetry for the same fraudulent WhatsApp Business phone number, enabling detection across both email and authentication channels. Note: message body content is not available in the EmailEvents schema, so fraud-phrase matching is subject-only.
Detects a specific adversary pattern termed 'Phantom Deal' where a user is socially engineered into disabling their VPN (by claiming a link won't open), followed immediately by a rapid succession of accesses to the same tracking or canary link from that user account. The rule correlates sign-in events indicating a shift in VPN or MFA context with subsequent bursts of URL clicks.
Detects anomalous sign-in behavior shortly after a successful MFA-authenticated session in Microsoft 365. This rule flags scenarios where a subsequent session for the same user occurs within a short window (30 minutes) from a different IP, ASN, User-Agent, or device identifier, potentially indicating the replay of a stolen session cookie obtained via Adversary-in-the-Middle (AiTM) phishing.
This rule monitors for network connections, firewall traffic, and Entra ID authentication events involving known malicious IP addresses (the 'Wall of Shame'). The rule specifically flags interactions occurring over common VPN ports, suggesting potential unauthorized access or persistence attempts via VPN services.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
This rule detects modifications to Group Policy Objects (GPO) or Microsoft Entra (formerly Azure AD) policies that weaken established security controls. For GPO, it monitors Event ID 5136 for changes to security-relevant attributes (e.g., disabling firewall or real-time monitoring) in Active Directory. For Entra, it monitors audit logs for administrative operations that reduce security posture, such as disabling MFA, lowering authentication trust, or deleting Conditional Access policies. It includes filters to exclude legitimate, documented change management activities.
This rule detects modifications to Group Policy Objects (GPO) or Microsoft Entra (formerly Azure AD) policies that weaken established security controls. For GPO, it monitors Event ID 5136 for changes to security-relevant attributes (e.g., disabling firewall or real-time monitoring) in Active Directory. For Entra, it monitors audit logs for administrative operations that reduce security posture, such as disabling MFA, lowering authentication trust, or deleting Conditional Access policies. It includes filters to exclude legitimate, documented change management activities.
This rule monitors for successful sign-ins to sensitive cloud resources (such as Microsoft Authentication Broker, Office 365 Exchange Online, or Graph API) that originate from IP addresses not observed in the user's recent history (14-day baseline) or from known datacenter/hosting network ranges. The rule also filters for common scripted User-Agent strings (e.g., Python requests, curl) or empty User-Agent strings to increase the likelihood of detecting programmatic or malicious automated access rather than standard browser-based user activity.
This rule detects potential session token replay attacks in Azure Active Directory by correlating interactive or single-factor sign-in events using 'python-requests' user agents (common in automated tooling) with subsequent 'Register device' and 'Register security info' (Windows Hello for Business) activity within a 48-hour window. This behavior often indicates an adversary attempting to register a device to a compromised account to maintain persistence or bypass MFA requirements.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
Detects anomalous authentication patterns indicative of session token replay attacks. The rule identifies instances where a user successfully performs an MFA-authenticated, interactive sign-in, followed shortly (within 5-60 minutes) by a single-factor sign-in for the same user. The suspicious activity is characterized by a shift to a different IP/ASN, an unmanaged device (non-trusted), and a change in browser or OS identifiers, all while the user's geolocation (city/country) remains consistent. This behavioral pattern is highly consistent with the use of residential proxy infrastructure to replay stolen session tokens, effectively bypassing MFA.
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