Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects successful OAuth application consent grants or service principal role assignments involving sensitive permissions, such as read access to mail, contacts, files, or directory information. This activity is a common indicator of OAuth-based phishing or unauthorized persistent access to cloud resources.
This rule detects when a user grants an OAuth application permissions within an Azure AD or Office 365 environment, specifically monitoring for highly sensitive permissions such as 'Mail.Read', 'Files.ReadWrite', 'User.Read.All', or 'offline_access'. The rule cross-references the application ID against a known list to filter out pre-authorized applications and assigns a risk score based on the combination of granted permissions, flagging suspicious, unrecognized applications.
Detects instances where a user grants an OAuth application permissions for high-privilege scopes such as 'mail.read', 'files.readwrite', or 'offline_access'. This behavior is frequently indicative of OAuth consent phishing campaigns targeting Microsoft Entra ID environments to gain unauthorized access to user data and maintain persistence via stolen access tokens.
Detects automated enumeration patterns via the Microsoft Graph API, specifically targeting bulk directory pulls (requests with $top=999) and keyword-based searches for sensitive organizational data (payroll, HR, finance). This rule aggregates activity by user session to identify suspicious volumes and diversity of requests.
This rule monitors Microsoft Entra ID (Azure AD) sign-ins for indicators associated with the 'Payroll Pirate' campaign. It identifies non-interactive OAuth/token-based authentication requests originating from residential Internet Service Provider (ISP) ASNs using devices marked as unmanaged. It further elevates risk by detecting impossible travel (same user accessing from multiple IPs in a short window) and the use of specific browser User-Agent strings (Firefox or Axios) characteristic of the threat actor's tooling.
Detects high-volume, suspicious enumeration of HR and Payroll related information via Microsoft Graph API. The rule identifies anomalous behavior such as rapid bulk pagination, usage of suspicious user agents, and specific targeting of sensitive fields (e.g., department, job title) or keywords commonly associated with HR and financial data, likely indicating the use of a stolen OAuth token.
This rule monitors for security alerts related to Azure AI services, specifically detecting credential theft attempts and LLM jailbreak attempts that have been blocked or detected by Azure's built-in content filtering mechanisms.
Detects Parameter-to-Prompt (P2P) injection attempts targeting Microsoft 365 Copilot by identifying suspicious patterns in URL query parameters. The rule monitors AuditLogs for queries containing HTML tags, encoded payloads, or known malicious markers typical of prompt injection exploits against search functionalities (CVE-2026-42824).
This rule detects network connections and user sign-ins originating from IP addresses identified as belonging to Iran. It also identifies sign-ins where the reported country is Iran, but the IP address is not found within the provided Iranian IP list, which could indicate IP geolocation discrepancies or obfuscation attempts.
This rule detects potential brute force or credential stuffing attacks against Azure AD by identifying multiple failed sign-in attempts followed by a successful sign-in from the same user and IP address within a short time frame (1 minute). It specifically looks for scenarios where the successful sign-in occurs after the failed attempts and involves different applications, excluding common Office 365 services to reduce noise.
This rule detects when a single user principal name (UPN) attempts five or more sign-ins from the same IP address within a one-hour window, and each sign-in is flagged with a 'RiskDetail' other than 'none' but still results in a 'Success' status. This could indicate an attacker attempting to bypass security controls or an account compromise where the attacker is repeatedly trying to access the account from a consistent location, possibly with different credentials or methods, until successful.
Detects a sequence of failed authentication attempts potentially indicative of an offline JWT secret brute-force attack (using tools like jwt_tool), followed by a successful authentication from the same source. This pattern suggests the adversary successfully recovered the secret, forged a valid token, and subsequently used it to gain unauthorized access.
Detects network requests to Microsoft Graph API that appear to be modifying authentication methods, specifically targeting phone-based multi-factor authentication settings. This may indicate an adversary attempting to register their own MFA device to a compromised account to maintain persistence or bypass MFA.
Detects high-frequency authentication failure events targeting multiple unique user accounts from the same source IP address within a 10-minute window. This behavior is indicative of password spraying or credential stuffing attacks against Azure Active Directory (Microsoft Entra ID). The rule specifically monitors for common error codes related to incorrect passwords or account lockout conditions.
This rule detects successful additions or updates to service principal credentials or application certificates/secrets within Azure AD. This activity can indicate persistence establishment by an attacker who has compromised an account with sufficient permissions to manipulate application identities.
Detects the creation of Kubernetes pods where the 'hostPID' or 'hostNetwork' settings are enabled. These configurations allow a pod to share the host's process namespace or network stack, respectively, which are common vectors for container escapes and host-level privilege escalation.
Detects the addition of users to specific high-value or sensitive groups in Microsoft Entra ID (Azure AD), which could indicate potential unauthorized privilege escalation or persistence attempts by an attacker.
This rule detects suspicious activity related to Azure Active Directory service principals. It specifically looks for a service principal performing multiple (5 or more within an hour) 'Add service principal', 'Add owner to application', or 'Add permission grant' operations. This pattern could indicate an attacker attempting to escalate privileges or establish persistence within an Azure AD environment by manipulating service principals and application permissions.
This rule detects an unusual spike in 'Export' or 'Download' operations within Azure Activity logs by a single caller. It triggers when a user performs 5 or more such operations within an hour, which could indicate data exfiltration attempts or suspicious data access patterns.
Detects anomalous device code authentication sessions originating from non-corporate IP addresses using common command-line user agents, which are immediately followed by a device registration event by the same user. This pattern is indicative of OAuth device code phishing, where an attacker tricks a user into authorizing a malicious application to access their account.
Detects high-volume, potentially automated enumeration of Microsoft Graph API endpoints targeting sensitive personnel data (payroll, HR, finance). This rule identifies requests using non-standard or suspicious user agents—such as curl, python-requests, or common web client patterns—when interacting with user and group directories in the Microsoft 365 environment, characteristic of the 'Payroll Pirate' (Storm-2755/Storm-2657) campaign patterns.
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