Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
461 detections
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Detects successful Device Code authentication followed immediately by a new device registration, a tactic used to extend access via PRT generation.
This rule detects when a non-administrative user grants an application high-privilege OAuth scopes (such as mail reading, file access, or directory management) within an Azure/Microsoft 365 environment. Such consent grants can be used by attackers to maintain persistence and bypass MFA by gaining delegated access to sensitive resources.
Detects a potential Conditional Access bypass, often associated with Storm-2372, where a device is registered and immediately followed by a PRT or deviceToken-authenticated sign-in to sensitive cloud applications within one hour. This behavior indicates the usage of non-TPM-attested 'phantom' devices to circumvent device-based security requirements.
Detects anomalous, non-interactive Microsoft Graph sign-in activity consistent with the Payroll Pirate session hijacking campaign. The rule flags instances where the same user account authenticates via Microsoft Graph using the 'Firefox/131.0' user agent from multiple distinct source IP addresses within a 6-hour window, indicating potential stolen session token replay from distributed proxy infrastructure.
This rule detects network traffic indicative of the 'EvilTokens' phishing kit, specifically targeting Microsoft OAuth Device Code flow. It looks for HTTP POST requests to the '/api/device/start' URI on domains hosted on Cloudflare Workers ('.workers.dev'). This pattern suggests an attempt to initiate a device code phishing attack, where adversaries trick users into entering credentials or codes to grant access to malicious applications.
This rule detects potential Conditional Access bypass attempts where a Primary Refresh Token (PRT) is exchanged for an Azure Active Directory (AAD) Graph token. The detection specifically looks for successful sign-ins to 'Windows Azure Active Directory' or 'Microsoft Graph' resources from devices marked as 'compliant' but with 'Unknown' ownership or no prior device registration history in Audit Logs. This could indicate an adversary using a compromised PRT on an unregistered or untrusted device to gain access to resources that should be protected by Conditional Access policies.
This rule detects attempts to bypass Conditional Access policies by exchanging a Primary Refresh Token (PRT) for an Azure Active Directory (AAD) Graph token on a device that is either of 'Unknown' ownership or lacks a check-in history, despite being marked as compliant. This behavior could indicate an adversary attempting to gain unauthorized access to resources by leveraging a compromised PRT on an unmanaged or suspicious device, circumventing Conditional Access controls.
Detects session hijacking attempts where a session cookie is used from a different IP address or user-agent immediately following a successful MFA authentication event. This behavior is indicative of an adversary replaying a stolen session token.
Detects automated programmatic token refreshes (BAV2ROPC) originating from Railway IP space. This rule specifically looks for sign-in logs in Azure Active Directory where the UserAgent contains 'BAV2ROPC' and the IPAddress falls within known Railway PaaS IP ranges.
Detects new app installations, expansions of OAuth scopes, or the addition of collaborators to Slack applications. These activities can indicate an adversary attempting to gain persistent access, escalate privileges, or exfiltrate data from Slack by leveraging malicious or compromised applications.
Detects successful non-interactive token acquisitions using specific Microsoft first-party application IDs known to bypass Entra Conditional Access Policies through Nested App Authentication (NAA/BroCI). The detection specifically targets sign-ins to the Microsoft Graph resource.
Detects a non-interactive sign-in using an existing session shortly after the user completes interactive MFA, which can indicate stolen token replay. This rule identifies scenarios where a user successfully completes an interactive multi-factor authentication (MFA) sign-in, and then, within a short time frame (1800 seconds or 30 minutes), a non-interactive sign-in occurs for the same user and session ID. This pattern is indicative of a stolen session token being replayed by an attacker, bypassing subsequent MFA prompts.
This rule detects when an application role assignment or delegated permission grant is successfully added to a service principal in Azure Active Directory, specifically looking for highly privileged permissions such as 'RoleManagement.ReadWrite.Directory', 'UserAuthenticationMethod.ReadWrite.All', 'UserAuthMethod-TAP.ReadWrite.All', or 'User.Read.All'. This could indicate an adversary attempting to gain elevated access or persistence within the Azure AD environment.
This rule detects network traffic indicative of the 'EvilTokens' phishing kit, specifically targeting Microsoft OAuth Device Code flow. It looks for HTTP POST requests to the '/api/device/start' URI on domains hosted on Cloudflare Workers ('.workers.dev'). This pattern suggests an attempt to initiate a device code phishing attack, where adversaries trick users into entering credentials or codes to grant access to malicious applications.
Detects successful Device Code authentication followed immediately by a new device registration, a tactic used to extend access via PRT generation. This behavior is indicative of an attacker using a stolen device code to register a new device, thereby gaining persistent access to the user's account.
Detects automated Microsoft Graph API requests indicative of the 'Payroll Pirate' campaign, specifically targeting payroll and HR personnel after initial access via AiTM session token theft. The rule identifies two malicious patterns: bulk user directory harvesting using '?$top=999' and keyword-targeted enumeration (payroll, human, compensation) using OR-chained search queries and pagination markers ($skiptoken).
Detects a browser session requesting a device code and repeatedly polling the token endpoint while the victim completes authentication elsewhere. This behavior is indicative of an adversary using a device code phishing technique, often associated with the Tycoon threat actor.
Detects when a single session identifier is used to access multiple cloud applications, where at least three distinct applications are accessed within an hour, and these applications were not part of the original interactive sign-in. This behavior can indicate a token replay attack, specifically as described in the Elastic Security Labs research on Tycoon 2FA AiTM detection engineering.
This rule detects attempts to grant consent to OAuth applications, which could indicate an illicit consent grant attack. It specifically looks for successful operations related to consenting to applications, adding app role assignments to service principals, adding delegated permission grants, or adding OAuth2PermissionGrants within audit logs. The rule extracts details such as the target application, the user who consented, their initiating IP address, and the permissions granted.
This rule detects EvilTokens device code OAuth phishing by identifying rapid, repeated POST requests to the /common/oauth2/token endpoint with a device_code grant and authorization_pending responses, followed by a successful token issuance and sign-in without an MFA claim. This pattern is consistent with EvilTokens session harvesting.
Detects successful non-interactive token acquisitions using specific Microsoft first-party application IDs known to bypass Entra Conditional Access Policies through Nested App Authentication (NAA/BroCI). The detection specifically targets sign-ins to the Microsoft Graph resource.
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