Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects unauthorized privilege escalation for AI agent identities within an orchestration platform. The rule triggers when an AI agent account receives an IAM role change, API scope grant, or tool permission update that lacks a corresponding human-approval audit event, or occurs shortly after the agent generates logs indicating potential prompt injection or anomalous behavior.
Detects the creation of scheduled tasks, recurring jobs, or webhook subscriptions by a user identity flagged as an AI_AGENT. This activity is monitored for persistence, especially when the event lacks a descriptive context or targets external networks, suggesting potential unauthorized agent behavioral drift or malicious persistence.
Detects activity from known Storm-3168 (JADEPUFFER) campaign IP addresses across Azure control-plane, sign-in, and App Service logs. The rule monitors for malicious indicators in Azure Activity logs, Azure Sign-in logs, and Service Principal sign-ins, as well as specific sensitive URI paths (e.g., shells, admin login paths) within App Service HTTP logs.
Detects a service principal attempting to delete multiple Azure SQL databases in a short timeframe, resulting in failures. This pattern is characteristic of malicious data destruction activity, such as that observed in Storm-3168 (JADEPUFFER) campaigns, but accounts for the possibility of misconfigured infrastructure-as-code pipelines by requiring a high volume of failed requests across distinct resources.
Detects a service principal or user account performing a burst of 'ListKeys' operations across multiple Azure Storage accounts. This behavior is indicative of an attacker attempting to dump access keys for multiple storage accounts after initial compromise or privilege escalation to gain further access to sensitive cloud data.
Detects a service principal or user account performing a burst of 'ListKeys' operations across multiple Azure Storage accounts. This behavior is indicative of an attacker attempting to dump access keys for multiple storage accounts after initial compromise or privilege escalation to gain further access to sensitive cloud data.
This rule detects reconnaissance activity targeting Azure App Service instances, specifically looking for attempts to access web-shell-like files, WordPress administration paths, PHP-CGI endpoints, or LangFlow code validation paths. It identifies potential Storm-3168 actor infrastructure through known IOCs or through patterns of high-volume, path-diverse HTTP requests that deviate from typical noise, helping to distinguish targeted probing from common internet background scanning.
Detects a precursor pattern identified as JADEPUFFER, where a failed 'ListKeys' operation (indicating an attempt to discover or access keys for a non-existent storage account) is immediately followed by a burst of destructive delete operations on critical cloud resources (e.g., storage, databases, key vaults) by the same actor.
Detects a coordinated, rapid deletion of a Key Vault, Function App, and App Service plan within the same resource group and time window by the same caller. This pattern is indicative of targeted destructive activity, such as that seen in the JADEPUFFER campaign, while explicitly excluding scenarios where the entire resource group is deleted, which is typical of routine IaC teardowns.
Detects a suspicious pattern often associated with Storm-3168 (JADEPUFFER) activity: prolonged, high-volume Azure resource enumeration by one service principal, followed shortly by a second service principal performing rapid, multi-subscription enumeration from the same source IP address.
Detects Azure sign-in events claiming successful hardware-key or FIDO2 authentication where the authentication issuer is not part of a known-good allow-list. This behavior is indicative of a rogue MFA provider, such as the TrustSink attack, which issues forged tokens claiming MFA requirements were satisfied.
Detects modifications to Microsoft Entra ID applications or service principals involving the addition or configuration of 'externalauthprovider' redirect URIs or properties. This behavior is indicative of an attacker attempting to establish a malicious federated identity or persistence mechanism by manipulating application configuration to use an adversary-controlled authentication provider.
Detects a suspicious sequence of identity-related operations in Azure AD, characterized by the modification of authentication methods policies followed by rapid application or service principal registration, consent granting, or role assignments by the same actor within a 10-minute window. This behavior often indicates an adversary attempting to establish persistence or escalate privileges via malicious OAuth applications or service principals after weakening security posture.
Detects a suspicious sequence of identity-related operations in Azure AD, characterized by the modification of authentication methods policies followed by rapid application or service principal registration, consent granting, or role assignments by the same actor within a 10-minute window. This behavior often indicates an adversary attempting to establish persistence or escalate privileges via malicious OAuth applications or service principals after weakening security posture.
This rule detects potentially malicious activity where an identity performs enumeration of Kubernetes secrets or configmaps and subsequently performs a search action within Slack from the same IP address within a one-hour window. This behavioral pattern is indicative of post-breakout reconnaissance, where a compromised identity or token is used to exfiltrate sensitive cloud configuration data and then perform internal reconnaissance in SaaS collaboration tools to identify further targets or credentials.
Single-source Sigma proxy for the authentication-persistence stage of the multi-stage device-code-phishing-to-Graph-collection chain (see the companion KQL correlation rule "Passkey Persistence: Device-Code Phishing to MFA Takeover and Graph Collection" for the full, threshold-gated, cross-table detection). Sigma has no join, temporal-windowing, or aggregation support, so this rule fires on the authentication-persistence event alone and does NOT enforce the device-code sign-in precursor or the subsequent Graph-activity burst - both required by the full correlation. Scoped to the two highest-signal operations only (new security-info registration, and any admin-initiated registration on another user's account) to cut noise from routine self-service profile edits.
Detects the multi-stage Microsoft cloud identity compromise chain reported by Microsoft Security Research (September 2026): a victim completes a successful Entra ID device-code sign-in (often induced by passkey-themed device-code phishing), the same identity's authentication/security info is registered or changed (MFA/passkey persistence) within 60 minutes (deduplicated to the earliest such event per sign-in), followed within 120 minutes by a burst of at least 25 successful, delegated-context Microsoft Graph API calls (Scopes claim populated, i.e. user-delegated permissions rather than pure application/client-credential access) spanning at least 3 distinct resource paths, exhibiting reconnaissance (>=5 requests against /users, /groups, /directoryRoles, /roleManagement, /applications, /servicePrincipals, /organization) and/or collection (>=10 requests against /messages, /mailFolders, /attachments, /drive, /drives, /sites, /lists, /search) patterns. Restricting to delegated (Scopes-bearing) Graph calls and requiring resource-path breadth removes the two largest false-positive sources: service-principal/application-only automation jobs (Roles-only tokens) and single-endpoint polling tools. Pure behavioral correlation across SigninLogs, AuditLogs, and MicrosoftGraphActivityLogs - no static IOCs. Flags whether Graph activity originated from an IP different from the original device-code sign-in IP as a strong pivot/session-reuse indicator.
This rule detects anomalous, high-volume activity from a single user account interacting with known public generative AI platforms (e.g., ChatGPT, Copilot, Claude). It uses a threshold-based approach on CloudAppEvents logs to identify potential reconnaissance or bulk information gathering activities which could signify unauthorized use or automated data scraping via AI interfaces.
This rule detects potential quishing (QR code phishing) attempts by identifying emails with one or more image attachments and minimal URL content, followed by a risky user authentication event within a 3-hour window. This behavior is indicative of an attacker attempting to harvest credentials via a malicious QR code that redirects the user to a phishing site.
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