Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 suspicious sequence of behavior where an Azure service principal authenticates and immediately performs broad reconnaissance (enumeration) across multiple subscriptions and resource types. This pattern is often indicative of an adversary using a compromised service principal credential to map out an environment.
This rule monitors Azure Active Directory service principal sign-in logs to identify authentication attempts from countries or Autonomous System Numbers (ASNs) that have not been observed in the entity's 14-day historical baseline. Such anomalous login behavior may indicate potential account compromise, token theft, or unauthorized use of service principal credentials.
Detects anomalous, high-volume enumeration activity (List/Get/Read operations) performed by a single identity across multiple Azure resource providers within a short time window, indicative of automated reconnaissance by a compromised service principal or managed identity.
Detects anomalous use of an LLM provider API key by identifying successful API requests originating from multiple distinct countries within a one-hour time window. This activity often indicates the potential theft and concurrent unauthorized use of an API token.
Detects the registration of new tools, plugins, or connectors into an AI agent's registry, particularly from unverified publishers or outside of sanctioned deployment windows. The rule also flags cases where these newly registered tools are immediately invoked with sensitive-scope permissions (e.g., admin, secrets, write), which is consistent with indicators of AI agent supply chain compromise or unauthorized tool injection.
Detects anomalous, high-volume file deletion, modification, or resource deletion operations performed by an identified AI agent service account within a short timeframe. This behavior is indicative of a compromised AI agent being leveraged for mass data destruction, ransomware activity, or disruptive configuration changes.
Detects successful OAuth device code sign-in attempts where the geographic location of the authentication does not match the user's historical baseline location. This is indicative of OAuth device code phishing, where a user is tricked into approving an authentication prompt for an attacker-controlled device.
Detects the use of open-source secret-scanning tools (e.g., TruffleHog) by identifying their specific User-Agent strings in AWS CloudTrail logs during GetCallerIdentity calls, followed by suspicious enumeration activity (ListBuckets, ListSecrets, ListAccessKeys) from the same source IP. This behavior is indicative of threat actors validating stolen credentials for unauthorized access to cloud resources.
Detects anomalous bursts of sts:GetCallerIdentity API calls, which are often used by adversaries to validate harvested or stolen AWS access keys. The rule monitors for a high frequency of such calls or a large number of distinct access keys being validated from IP addresses that are not part of the organization's approved corporate or cloud egress ranges.
Detects Azure AD sign-in events indicative of 'EvilTokens' phishing-as-a-service tradecraft. The rule monitors for initial token-grant events (device-code authentication or OAuth application consent) and subsequent successful sign-ins using existing SessionIds. This rule is designed as a foundational detection component for identifying session token replay, which allows adversaries to bypass MFA and password requirements by hijacking valid session tokens.
Detects a multi-stage exfiltration sequence consisting of: (1) bulk file archival/compression using common utilities, (2) suspicious OAuth grant or service principal authorization, and (3) abnormal network egress volume to common ports. This pattern suggests an adversary is preparing data, establishing or leveraging an identity/application for cloud access, and subsequently exfiltrating data.
Detects suspicious AI agent behavior by identifying two primary scenarios: 1) The invocation of sensitive tools (e.g., code execution, file deletion) within a short timeframe following a flagged prompt injection or jailbreak attempt in the same conversation; or 2) The invocation of a tool by an AI agent that is not explicitly defined in its allowed tool list for the given workflow.
Detects high-velocity, automated-paced burst of deletion operations spanning multiple distinct Azure resource types (Storage, SQL, Key Vault, Web Sites) within a 15-minute window. This behavior is indicative of agentic AI-orchestrated cloud resource destruction, contrasting with typical administrative lifecycle management.
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 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.
Detects anomalous bursts of deletion activity targeting Azure Site Recovery and Backup resources, including management locks and backup policies. This behavior is consistent with an adversary attempting to inhibit system recovery capabilities, often a precursor to destructive activities such as ransomware deployment. The rule also correlates this activity with the deletion of other critical infrastructure components like databases or storage accounts.
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 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 attempts to delete Azure resource locks protecting Site Recovery or Backup services, followed by credential retrieval (ListKeys) within a one-hour window. This sequence pattern is a strong indicator of an adversary attempting to disable backup protection before potentially destroying data or exfiltrating keys.
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.
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