Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential cloud resource hijacking (e.g., cryptojacking) by monitoring for a sudden spike in the deployment of Azure virtual machines by a single user. It triggers if a user creates five or more virtual machines in a 10-minute window, specifically looking for deployments in regions where the user has not recently created VMs, or deployments utilizing high-compute SKUs commonly targeted for cryptocurrency mining.
This rule monitors successful operations related to Azure Traffic Manager within Azure Activity logs. It summarizes the count of such operations by the caller and time, ordered by the most recent activity. This can be used to track administrative actions or changes made to Traffic Manager configurations.
This rule detects an unusual number of successful encryption-related operations performed by a single caller within a one-hour window in Azure Activity logs. This could indicate legitimate bulk administrative tasks or potentially malicious activity such as data encryption for impact (e.g., ransomware) or preparation for exfiltration by an attacker.
This rule detects a spike in modifications or creations of Azure Diagnostic Settings within a one-hour window. A high volume of 'Diagnostic Setting' operations by a single caller could indicate an attempt to alter logging configurations, potentially to impair defenses or hide malicious activity.
This rule detects potentially malicious modification or configuration changes to Azure Function Apps. It monitors for operations such as creation, updates, and configuration changes that contain suspicious indicators like hardcoded credentials (TOKEN, SECRET, PASS), potential reverse shell patterns, or large Base64 encoded payloads. The rule specifically excludes known CI/CD pipeline callers to minimize false positives.
Detects anomalous activities targeting SaaS CRM applications (Salesforce, Microsoft Dynamics 365, HubSpot), including high-volume bulk exports, off-hours access, mass API queries for sensitive objects, and suspicious OAuth token grants.
Detects instances where a user or service principal is assigned to high-privilege roles (e.g., Global Administrator, Owner) without utilizing the Microsoft Entra Privileged Identity Management (PIM) service. This is indicated by the absence of 'PIM' in the LoggedByService field for a successful 'Add member to role' operation, which could signify an attempt to bypass established access controls and gain unauthorized elevated persistence.
This rule detects potentially malicious modification or configuration changes to Azure Function Apps. It monitors for operations such as creation, updates, and configuration changes that contain suspicious indicators like hardcoded credentials (TOKEN, SECRET, PASS), potential reverse shell patterns, or large Base64 encoded payloads. The rule specifically excludes known CI/CD pipeline callers to minimize false positives.
Detects a sequence of events where a cloud storage bucket is deleted and then immediately recreated with the same name. This pattern is indicative of a potential bucket hijacking attack, where an adversary attempts to take ownership of a bucket to intercept data streams, such as logging sinks, application data, or replication traffic.
Detects anomalous AWS API activity following a console login where the API calls originate from a different IP address within 10 minutes, potentially indicating the replay of stolen session tokens captured via Adversary-in-the-Middle (AiTM) techniques.
Detects anomalous device registration in Azure AD where a device code flow is used to authenticate to the Device Registration Service (DRS) and the resulting device is registered with an 'Unknown' or 'Linux' operating system. This behavior is indicative of an adversary, such as Storm-2372, using tools like AADInternals to perform phantom device registration to bypass conditional access policies by simulating a device without TPM attestation.
This rule detects potentially malicious activities involving Microsoft Copilot and Microsoft Graph, specifically focusing on unauthorized mailbox access via non-interactive sessions and patterns indicative of Server-Side Request Forgery (SSRF) during search operations. It monitors for anomalous interaction with the Graph API, specific Copilot search parameters, and suspicious image search requests.
Detects the execution of 'aws sts get-caller-identity' by common IDEs or code editor helper processes. This activity is often used by adversaries to verify the current AWS identity and permissions after gaining access to a developer's workstation.
Detects the execution of AWS CLI commands by common scripting interpreters (Node.js or Python). This behavior is often indicative of automated cloud environment reconnaissance or credential testing using compromised access keys or instances.
This rule monitors network traffic for suspicious patterns indicating exploitation of LocalStack environments. It detects three primary malicious activities: Velocity Template Language (VTL) injection targeting reflection methods (e.g., ProcessBuilder) for RCE; unauthorized manipulation of API Gateway resources (e.g., creating or modifying deployments) accompanied by IAM scope bypass techniques; and direct execution of RCE-style API triggers against known LocalStack port 4566.
Detects suspicious app installations, custom app creation, and bot additions within Microsoft Teams. This rule identifies activities such as sideloaded app installations, which can bypass standard vetting processes and serve as a persistence mechanism for attackers. It also flags custom app creation outside of typical development teams, which could indicate the deployment of command and control (C2) bots or data exfiltration applications. Additionally, the rule looks for the addition of bots to teams and suspicious keywords in app names that might suggest impersonation or malicious tooling.
Detects the creation or deletion of Kubernetes namespaces and nodes via the API server. This activity can indicate an adversary attempting to establish persistence, expand their control, or disrupt the environment within a Kubernetes cluster.
Detects attempts to list, read, create, update, or delete Kubernetes secrets via the Kubernetes API server. This activity can indicate an adversary attempting to gain access to sensitive information or manipulate the environment.
Detects rapid high-volume file and messaging operations across multiple Microsoft 365 services (SharePoint, OneDrive, Teams, Exchange) within a compressed 10-minute window from a single identity and IP address. This behavior can indicate data exfiltration or reconnaissance by an adversary.
Detects SMS pumping attacks via bulk SMS API requests
Detects bulk AWS or Azure API command execution via CLI tools
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