Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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IDS Classtypes
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Detects potentially suspicious explicit credential logon events where the user
is trying to logon with explicit credentials (username and password) that are
different from the current user context. It might indicate an attacker attempting
to escalate privileges after obtaining credentials for a different user account.
is trying to logon with explicit credentials (username and password) that are
different from the current user context. It might indicate an attacker attempting
to escalate privileges after obtaining credentials for a different user account.
This rule detects potential Adversary-in-the-Middle (AiTM) activity by correlating network events indicating a connection to a known phishing domain with subsequent suspicious authentication behavior. Specifically, it identifies sessions associated with non-corporate IP addresses that show evidence of token reuse (e.g., multiple distinct IP addresses for the same session identifier) occurring within a short window after accessing a phishing portal.
Detects interactive sign-in attempts for accounts commonly associated with Microsoft sync services (e.g., AD Connect, MSOL sync). Service accounts should typically perform background, non-interactive authentication. An interactive login for these accounts may indicate credential misuse or unauthorized access.
This rule detects Kerberos Service Ticket (TGS) requests made for the 'AZUREADSSOACC$' computer account, which is typically used for Seamless Single Sign-On (SSO) in hybrid Azure AD environments. The rule explicitly excludes known Domain Controllers from triggering the alert to focus on potentially suspicious TGS requests originating from other systems.
Detects interactive sign-in attempts for accounts commonly associated with Microsoft sync services (e.g., AD Connect, MSOL sync). Service accounts should typically perform background, non-interactive authentication. An interactive login for these accounts may indicate credential misuse or unauthorized access.
This rule detects Kerberos Service Ticket (TGS) requests made for the 'AZUREADSSOACC$' computer account, which is typically used for Seamless Single Sign-On (SSO) in hybrid Azure AD environments. The rule explicitly excludes known Domain Controllers from triggering the alert to focus on potentially suspicious TGS requests originating from other systems.
This rule identifies successful user sign-ins originating from IP addresses associated with residential or commercial VPN ASNs that have not been observed in the user's historical sign-in data (past 30 days). By comparing current activity against a baseline of known user locations, it flags potentially unauthorized access through masked connections.
Detects login or authentication attempts to a Cisco Firewall Management Center (FMC) management interface from non-authorized source IP addresses. The rule specifically flags connections targeting potential low-privilege or service accounts that may indicate unauthorized access attempts or brute-force behavior directed at critical network infrastructure.
Detects login or authentication attempts to a Cisco Firewall Management Center (FMC) management interface from non-authorized source IP addresses. The rule specifically flags connections targeting potential low-privilege or service accounts that may indicate unauthorized access attempts or brute-force behavior directed at critical network infrastructure.
attackers are continuously abusing Device Code phishing, convincing victims to authenticate using the legitimate Microsoft login page. The victim completes the password and MFA correctly, but the resulting tokens are delivered to the attacker.
And one point that I think is important: Device Code Flow should not be enabled if you don't really need it. The recommendation is clear: disable it where possible and only allow documented exceptions.
The KQL below takes Cmsi:Cmsi as a reference (which means a Device Code Authentication flow was used) point and looks 15 minutes backwards (the time that a Code is valid) for the same user, grouping the authentication flow together with countries, IPs, browsers and User-Agents. The aim is to identify authentication flows where we observe different Browsers, Countries, IPs or User-Agents, potentially showing the transition between the victim and attacker context.
The idea is simple: Look at the complete authentication sequence and identify what changes between the victim and attacker context.
And one point that I think is important: Device Code Flow should not be enabled if you don't really need it. The recommendation is clear: disable it where possible and only allow documented exceptions.
The KQL below takes Cmsi:Cmsi as a reference (which means a Device Code Authentication flow was used) point and looks 15 minutes backwards (the time that a Code is valid) for the same user, grouping the authentication flow together with countries, IPs, browsers and User-Agents. The aim is to identify authentication flows where we observe different Browsers, Countries, IPs or User-Agents, potentially showing the transition between the victim and attacker context.
The idea is simple: Look at the complete authentication sequence and identify what changes between the victim and attacker context.
This rule detects the creation of a local user account named _BootUEFI_ and its addition to the Remote Desktop Users group, followed by RemoteInteractive logons using that account. This behavior is indicative of an RDP backdoor mechanism associated with the HeptaX campaign.
Detects high volumes of authentication failures within Okta, characterized by a single source IP address targeting a large number of distinct user accounts. This behavior is indicative of automated credential attacks, such as password spraying or credential stuffing, designed to discover valid credentials or exploit reused passwords while attempting to evade account lockout thresholds.
This rule analyzes Microsoft Entra (Azure AD) sign-in logs over a 30-day period for access to sensitive administrative applications (e.g., Azure Portal, Microsoft Intune, Defender). It flags user-application-IP sessions that exhibit unusual characteristics, such as login successes following failures, access from multiple geographic locations, or the use of multiple client types, which may indicate account compromise or unauthorized access.
Detects a Telegram account session being authorized from a new device/IP, which BlueNoroff has been observed abusing as the precursor step in the GhostCall self-propagation pipeline: operators reuse stolen/hijacked Telegram session cookies from a new device or IP, then use the hijacked session to send fake meeting invites to trusted contacts, enabling cyclical propagation to subsequent victims.
This rule only detects the session authorization event in isolation. Analysts should correlate matches on this rule with a companion rule that detects rapid meeting-invite fan-out for the same UserId occurring within roughly 15 minutes, since that cross-event correlation cannot be expressed within a single Sigma detection. A standalone match here does not confirm active self-propagation and requires that follow-up correlation to raise confidence.
This rule only detects the session authorization event in isolation. Analysts should correlate matches on this rule with a companion rule that detects rapid meeting-invite fan-out for the same UserId occurring within roughly 15 minutes, since that cross-event correlation cannot be expressed within a single Sigma detection. A standalone match here does not confirm active self-propagation and requires that follow-up correlation to raise confidence.
Detects Microsoft Entra ID sign-in events using the Resource Owner Password Credentials (ROPC) flow where the client application displays a blank name. This pattern is commonly associated with attackers spoofing OAuth client IDs to bypass security controls or perform user enumeration.
Detects the remote_logon C2 command token correlated with an absence of a matching auth event, indicating passive logon-session enumeration.
Detects high-frequency Resource Owner Password Credentials (ROPC) authentication attempts originating from a single IP address against multiple different user accounts within a 15-minute window. This behavior is indicative of a password spraying or brute force campaign targeting cloud authentication services.
Detects Remote Interactive RDP logon events targeting systems identified as servers or critical infrastructure, using the DeviceLogonEvents data source.
This rule serves as an investigation framework for Microsoft Entra ID sign-in events. It enables security analysts to filter, normalize, and inspect user authentication activities, including sign-in types (interactive/non-interactive), device management status, user risk levels, and conditional access status. The query is designed for incident response and forensic analysis rather than automated alerting.
Detects the execution of known Active Directory enumeration scripts or commands via PowerShell shortly after a Remote Desktop (RDP) login session is established on a device. This pattern is indicative of an attacker who has gained remote access and is immediately performing discovery activities.
Detects high-volume, anomalous authentication failure patterns originating from a single IP address, characterized by a large number of distinct applications and users accessed within a one-hour window. This is indicative of potential automated credential-based attacks such as password spraying or brute force.
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