Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
771 detections
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Detects anomalous authentication behavior where a user successfully completes an OAuth device-code grant, followed by a subsequent login event using the same user context but originating from a different source IP address. This pattern is indicative of device-code phishing, where an adversary tricks a user into authorizing a device, then uses the resulting session or token from their own infrastructure.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects anomalous sign-in behavior where a device code authentication flow is initiated from one location, but the resulting session is replayed from a different IP address in a different country within a one-hour window. This behavior is indicative of an adversary capturing an authentication token via a device code phishing or relay attack and attempting to use it from their own infrastructure to bypass conditional access policies and MFA.
Detects potential device code authentication phishing attacks by correlating a successful device code authentication event with a subsequent non-interactive sign-in from a suspicious user agent (Python Requests or specific Outlook versions) within a 10-minute window. This behavior is indicative of an adversary using a device code phishing lure to capture a token or session, followed by automated access via a script or impersonated client.
This rule detects potentially malicious activity where a user performs a device code authentication followed by multiple rapid token exchanges (often of different types) within an extremely short time window. This pattern is indicative of an attacker attempting to leverage a compromised device code grant to programmatically retrieve access or refresh tokens before the user has completed a legitimate flow or to automate malicious access.
This rule detects potential OAuth 2.0 device code phishing attempts by monitoring network activity for requests to common Microsoft OAuth device authorization endpoints. It flags requests that utilize a specific hardcoded client_id associated with known suspicious application registrations, combined with requested scopes for graph.microsoft.com and a Python-based user agent. This behavior is indicative of an adversary attempting to gain unauthorized access by tricking a user into authorizing a malicious application.
Detects an Azure AD Device Code authentication event followed within 60 seconds by a non-interactive Primary Refresh Token (PRT) sign-in event from the same user. This sequence is characteristic of adversary-in-the-middle (AiTM) phishing attacks where a user is tricked into authorizing a device code, and the adversary immediately leverages the resulting session/token to obtain a PRT for persistent access.
This rule detects potential OAuth 2.0 device code phishing attempts by monitoring network activity for requests to common Microsoft OAuth device authorization endpoints. It flags requests that utilize a specific hardcoded client_id associated with known suspicious application registrations, combined with requested scopes for graph.microsoft.com and a Python-based user agent. This behavior is indicative of an adversary attempting to gain unauthorized access by tricking a user into authorizing a malicious application.
Detects instances where a user successfully authenticates using the OAuth Device Code flow followed by subsequent mailbox operations (such as reading, sending, or deleting items) from a different IP address within a 10-minute window. This behavior is a strong indicator of adversary-in-the-middle phishing attacks where an attacker captures a session token and utilizes it from a remote location.
This rule detects potential abuse of the device code authentication flow by correlating a successful device code login with a subsequent non-interactive sign-in using the 'python-requests' user agent for the same user within 10 minutes. This behavior is indicative of an attacker programmatically accessing resources or APIs immediately after gaining authorization via a device code phishing or relay attack.
This rule detects potential abuse of the device code authentication flow by correlating a successful device code login with a subsequent non-interactive sign-in using the 'python-requests' user agent for the same user within 10 minutes. This behavior is indicative of an attacker programmatically accessing resources or APIs immediately after gaining authorization via a device code phishing or relay attack.
Detects anomalous sign-in activity originating from the Microsoft Authentication Broker or utilizing the OAuth device code flow, which are frequently abused by adversaries to perform OAuth phishing and obtain access tokens.
Detects non-interactive Entra ID sign-ins utilizing the python-requests library, which suggests an automated polling mechanism. This is indicative of 'GhostCode' or similar device code phishing attacks where an adversary uses a stolen device code token to programmatically poll for a successful authorization grant.
Detects a successful user authentication event following a Microsoft OAuth 2.0 device authorization grant flow. This detection identifies scenarios where a user may have been phished into entering an attacker-supplied device code on a malicious Microsoft device login page, resulting in the attacker successfully obtaining OAuth tokens.
Detects malicious OAuth 2.0 device authorization grant requests directed at Microsoft services. This rule identifies usage of specific App IDs associated with the Microsoft Authentication Broker combined with the 'offline_access' Graph scope, a pattern indicative of GhostCode-style phishing campaigns designed to steal access and refresh tokens.
This rule detects activities associated with the GhostCode phishing kit, which leverages a device-code phishing flow. It identifies malicious URLs interacting with harvester APIs to retrieve codes, email-delivered lures containing specific phishing markers ('userCodeDisplay', 'Verified Enterprise'), and corresponding endpoint/browser telemetry showing the rendered phishing page elements.
Detects potential device code phishing activity by identifying a successful device code authentication event followed shortly (within 10 minutes) by an interactive or API sign-in from the same user utilizing a Python-requests user agent, which is commonly associated with adversary-in-the-middle phishing kits.
Detects a sequence of events starting with a device code OAuth sign-in, followed within two hours by the creation or modification of inbox rules and high-frequency enumeration of email items (contacts, folders, messages, threads, people) via Microsoft Graph API. This behavior is indicative of post-compromise activity where an adversary uses OAuth device code grants to maintain access and subsequently automates inbox analysis or data harvesting.
Detects a sequence of events starting with a device code OAuth sign-in, followed within two hours by the creation or modification of inbox rules and high-frequency enumeration of email items (contacts, folders, messages, threads, people) via Microsoft Graph API. This behavior is indicative of post-compromise activity where an adversary uses OAuth device code grants to maintain access and subsequently automates inbox analysis or data harvesting.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
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