Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
772 detections
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Detects network requests to the Google OAuth device authorization flow endpoint, which is commonly abused in phishing campaigns to trick users into authorizing a malicious application on their behalf, allowing an attacker to steal session tokens.
Detects successful authentication events using the OAuth device code flow. This flow is often abused by adversaries to perform OAuth phishing, where a user is tricked into authorizing a malicious application, granting it access tokens to cloud resources.
Detects AWS credentials or config file reads by scripting engines (Python/Node/Ruby/etc.) excluding known AWS tooling, matching the mrmustard stealer's credential-theft behavior.
Detects network requests to the Google OAuth device authorization flow endpoint, which is commonly abused in phishing campaigns to trick users into authorizing a malicious application on their behalf, allowing an attacker to steal session tokens.
Detects anomalous sign-in behavior where a single unique token identifier is used from multiple IP addresses, countries, or devices within a short timeframe (less than one hour). This pattern is often indicative of session token theft, where an adversary uses an exfiltrated token to authenticate from a different location or device, bypassing standard credential-based authentication.
Detects successful authentication events using the OAuth device code flow. This flow is often abused by adversaries to perform OAuth phishing, where a user is tricked into authorizing a malicious application, granting it access tokens to cloud resources.
Detects AWS credentials or config file reads by scripting engines (Python/Node/Ruby/etc.) excluding known AWS tooling, matching the mrmustard stealer's credential-theft behavior.
This rule detects potential OAuth Device Code Flow phishing attacks where users are directed to malicious lure pages on romnor[.]ca to enter a Microsoft device code. It also alerts on authentication activity associated with a specific malicious OAuth client ID (d3590ed6-52b3-4102-aeff-aad2292ab01c) known to be used by a phishing backend to poll and claim OAuth tokens.
This rule monitors container logs for attempts to access the Azure Instance Metadata Service (IMDS) via the 169.254.169.254 endpoint to request OAuth tokens or access Azure Key Vault secrets. Such activity within a containerized environment is often indicative of credential theft or discovery attempts by an adversary attempting to escalate privileges using the container's managed identity.
Detects suspicious use of the OAuth 2.0 device code authentication flow. The rule identifies potential token harvesting and phishing attempts by flagging device code sign-ins that originate from unusual user agents, unknown IP addresses or ASNs, unrecognized applications, or for users who have not previously utilized device code authentication. Legitimate, first-party applications like Azure CLI and Azure PowerShell are explicitly excluded to minimize noise.
Detects process command lines using curl to query the Azure Instance Metadata Service (IMDS) endpoint (169.254.169.254) for OAuth tokens. This behavior is indicative of an attacker attempting to leverage an Azure Managed Identity associated with a compromised virtual machine to obtain temporary security tokens for unauthorized access to other Azure resources.
Detects potential misuse of an Azure Managed Identity token on a Linux host, where 'curl' is used to interact with the Azure Key Vault API (vault.azure.net/secrets) while presenting an Authorization bearer token. This pattern can indicate an adversary who has obtained a Managed Identity token (e.g., via the Instance Metadata Service) and is attempting to exfiltrate or access sensitive secrets stored in Azure Key Vault.
Detects a sign-in failure with error code 50199 (indicating a device-code interrupt/waiting state) followed immediately by a successful sign-in from the same source IP address. This pattern is characteristic of device-code phishing attacks, where an attacker intercepts a device code and completes the authentication process on behalf of the victim.
Detects Microsoft Entra ID sign-in events using the non-interactive OAuth device-code protocol against the 'common' tenant endpoint where MFA was not applied. This behavior is consistent with OAuth device-code phishing campaigns (e.g., Storm-2372/DEBULL) that exploit Conditional Access device-code flow allowances to bypass standard authentication controls.
ARTokenC2NetworkTraffic - fully-featured phishing-as-a-service (PhaaS) operator panel, branded "ARToken," that shares infrastructure, API contracts, and operational patterns with the EvilTokens platform.
This rule detects suspicious sign-in patterns indicative of an EvilTokens-style Microsoft Device Code OAuth phishing attack. It identifies successful device code flow sign-ins where Multi-Factor Authentication (MFA) was not applied or satisfied, suggesting an adversary has bypassed MFA using a stolen device code. The rule aggregates these suspicious sign-ins by user, listing associated applications, IP addresses, and locations for analyst review.
Detects potentially malicious use of the device code authentication flow in Entra ID sign-in logs. The rule correlates device code usage with indicators of suspicious activity, such as rare User-Agent strings (e.g., 'python-requests') often used in phishing/relay toolkits, or sign-ins flagged by Azure AD Identity Protection as risky. It includes exclusions for known first-party Azure CLI and PowerShell clients to minimize noise from legitimate administrative activity.
Detects Azure CLI operations creating or modifying an Azure Container Registry (ACR) Task with an attached managed identity, where the task definition references Key Vault secrets. This pattern is used to abuse ACR Task automation and its managed identity to exfiltrate Key Vault secrets.
Detects the Cursor IDE (Cursor.exe) or its child processes accessing sensitive SSH private key files or cloud provider authentication credentials. This behavior is indicative of a compromised IDE process, potentially leveraging malicious extensions or MCP (Model Context Protocol) servers to exfiltrate secrets from the local filesystem.
Detects HTTP POST requests containing 'poll_auth_broker_token' and 'device_code' parameters, which are characteristic of malicious OAuth 2.0 device authorization grant flows commonly used in phishing campaigns.
This rule detects HTTP POST requests to known phishing domains (frenksv.sbs, debull.app) which include specific parameters indicative of an attempt to initiate the OAuth 2.0 device authorization grant flow ('get_auth_broker_device_code'). This pattern is associated with phishing campaigns aiming to hijack a user's session by tricking them into authorizing a malicious application, eventually leading to the theft of application access tokens.
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