Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects successful sign-in attempts to Azure AD (Entra ID) using the Device Code authentication protocol. Device Code flow allows users to sign in to input-constrained devices by using a browser on another device. While legitimate for smart TVs, IoT devices, or CLI tools, this flow is frequently abused by attackers to perform phishing or bypass MFA by tricking users into authorizing an application.
This rule aggregates Azure AD sign-in logs for a specific application, grouping by user principal name, IP address, location, and device ID. It provides a baseline view of user authentication patterns to identify unusual sign-in activity such as anomalous login locations or device usage.
Detects anomalous activity in Microsoft Graph API logs where a single identity (user or application) performs a high volume of requests across multiple sensitive administrative categories, such as directory role management, authentication method modification, application or service principal changes, and OAuth consent operations. This pattern is indicative of potential unauthorized reconnaissance, privilege escalation, or persistence attempts within an Azure/Microsoft 365 environment.
Detects login events to the 'My Sign-Ins' portal (mysignins.microsoft.com) by users. This portal is a high-value target for adversaries who have gained access to a session via token theft or session hijacking, as it allows them to modify or add authentication methods (such as MFA devices) to establish long-term persistence in the victim's account.
This rule detects a suspicious Azure sign-in sequence, identified by error code 50074 (User failed MFA) followed by 50140 (This error occurred due to 'Keep me signed in' interrupt when the user was authenticating). This pattern is indicative of an Adversary-in-the-Middle (AiTM) phishing attack where the attacker is attempting to bypass MFA or manipulate session persistence after capturing initial credentials.
Detects sign-in activity to the 'Office Home' portal from an unmanaged, non-compliant device, followed by authentication to sensitive cloud services like SharePoint Online, OneDrive, or Microsoft Graph. This pattern often indicates a potential session hijacking or post-compromise activity where an attacker uses an unmanaged device to access enterprise data via cloud application discovery.
This rule identifies instances where a user successfully authenticates using a phone app OTP MFA method that was registered between 1 and 30 days prior. The rule specifically flags logins associated with potentially automated or non-browser user agents, or logins flagged with risk, suggesting potential account takeover or persistence mechanisms involving MFA re-registration.
Detects a suspicious pattern where a user registers a new PhoneAppOTP MFA method and subsequently logs in using this method after a significant time delay (exceeding 3 days). This behavior is indicative of an attacker who has gained temporary access, registered their own MFA device to ensure persistent future access, and returned later to utilize it.
Detects a suspicious pattern where a user registers a new PhoneAppOTP MFA method and subsequently logs in using this method after a significant time delay (exceeding 3 days). This behavior is indicative of an attacker who has gained temporary access, registered their own MFA device to ensure persistent future access, and returned later to utilize it.
This rule detects suspicious Azure AD sign-in activity originating from a single user account that utilizes the 'deviceCode' authentication protocol while simultaneously exhibiting activity from multiple distinct and highly specific User Agent strings (Python requests library and Microsoft Outlook 16.0.17425). This pattern is indicative of potential token theft or automated credential harvesting where a legitimate OAuth flow is subverted to gain persistent access.
Detects Google Workspace login activity that's classified as suspicious by Google.
This rule identifies successful user sign-in events specifically targeted at Microsoft's management portals (myaccount.microsoft.com and mysignins.microsoft.com). It aggregates these events by user, tracking the frequency, timeframe, and originating IP addresses for successful access. This monitoring is useful for detecting abnormal access to identity settings, which could indicate credential abuse or unauthorized account management.
Detects multiple anomalous sign-in events using the device-code authentication flow within an Entra ID tenant. The rule correlates sign-ins from geographically disparate IP addresses (often associated with known attacker infrastructure or proxies) using device-code flows, which is a technique used in 'ARToken' style phishing campaigns to compromise multiple user accounts in a short timeframe.
Detects the creation of new AWS access keys or login profiles for a target identity immediately following the deletion or modification of a credential for the same identity, where the actors performing the two actions are different. This pattern indicates an adversary creating persistent access after a security incident responder or automated system has revoked a previously compromised credential.
Detects a suspicious sequence of events within JFrog Artifactory where an account accesses sensitive code-signing material (rubygems/gemspec/signing keys) and subsequently performs administrative actions (user addition/role assignment/privilege escalation) within a one-hour window, indicating potential account takeover or exploitation.
Detects a suspicious sequence of events within JFrog Artifactory where an account accesses sensitive code-signing material (rubygems/gemspec/signing keys) and subsequently performs administrative actions (user addition/role assignment/privilege escalation) within a one-hour window, indicating potential account takeover or exploitation.
Detects pull requests created in GitHub repositories by entities labeled as 'Bot', 'App', or 'integration', or containing the term 'codex', specifically targeting repositories where such entities have not performed these actions in the previous 30 days. This baseline approach identifies potentially hijacked or unauthorized automation accounts performing activities outside of their standard repository scope.
Detects pull requests created in GitHub repositories by entities labeled as 'Bot', 'App', or 'integration', or containing the term 'codex', specifically targeting repositories where such entities have not performed these actions in the previous 30 days. This baseline approach identifies potentially hijacked or unauthorized automation accounts performing activities outside of their standard repository scope.
Detects pull requests created in GitHub repositories by entities labeled as 'Bot', 'App', or 'integration', or containing the term 'codex', specifically targeting repositories where such entities have not performed these actions in the previous 30 days. This baseline approach identifies potentially hijacked or unauthorized automation accounts performing activities outside of their standard repository scope.
This rule detects a user account performing its first-ever GitHub OAuth or repository access within a short timeframe (30 minutes) after authenticating to a designated low-trust OpenAI community forum. This pattern is designed to identify potential adversary activity where a compromised or newly created account is used to pivot from a low-trust environment to corporate repository access.
This rule detects a user account performing its first-ever GitHub OAuth or repository access within a short timeframe (30 minutes) after authenticating to a designated low-trust OpenAI community forum. This pattern is designed to identify potential adversary activity where a compromised or newly created account is used to pivot from a low-trust environment to corporate repository access.
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