Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of 'aws sts get-caller-identity' spawned by IDE-related processes such as VS Code extension hosts or Amazon Q language servers. This pattern may indicate cloud credential reconnaissance performed by a malicious MCP (Model Context Protocol) server or compromised development extension (CVE-2026-12957).
This rule detects network events where a device attempts to access the Kubernetes API '/api/v1/namespaces/*/secrets' endpoint. This activity could indicate an attempt to enumerate or exfiltrate sensitive information (secrets) stored within Kubernetes, potentially by an attacker who has gained initial access to a pod or compromised a service account.
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.
Detects high-impact configuration changes to Azure management groups or subscriptions (e.g., write/delete operations) that are performed by non-privileged accounts or outside of defined business change windows. This activity can indicate unauthorized privilege escalation, resource manipulation, or reconnaissance by an adversary.
Detects the execution of 'aws sts get-caller-identity' from unexpected or potentially suspicious parent processes such as Node.js, bash/sh, or IDE-related processes like VS Code or Amazon Q. This command is often used by developers to confirm identity, but when triggered from these contexts, it may indicate unauthorized access or exploration by an adversary operating within a development environment.
Detects execution of AWS STS commands to identify the caller's identity in conjunction with suspicious outbound POST requests. This pattern is commonly used by adversaries to verify compromised cloud credentials or enumerate permissions within an AWS environment.
Detects unauthorized or suspicious AWS CLI operations and sensitive IAM API calls initiated from developer tooling processes like VS Code (including the Amazon Q extension host). This behavior is often associated with the exploitation of MCP (Model Context Protocol) auto-execution vulnerabilities, where attackers attempt to use compromised developer environments to escalate privileges or exfiltrate cloud credentials.
Detects attackers querying audit logs to understand defender visibility
This rule detects persistent Microsoft 365 access established by an attacker using OAuth refresh tokens, typically following a device_code phishing attack. It correlates three key events: initial device_code sign-ins from non-compliant or non-managed devices, the subsequent consent to a new OAuth application (likely attacker-controlled) from the same user and within a short timeframe, and finally, Microsoft Graph mail API access originating from that newly registered application. This sequence indicates an adversary has successfully phished a user, gained consent for a malicious application, and is now using it to access the user's mailbox data.
This rule detects potentially suspicious AWS API activity by identifying IAM identities that perform high-privilege operations or use developer-oriented user agents (e.g., boto3, python-requests) from multiple distinct IP addresses within a one-hour window. It calculates a risk score based on the combination of source IP diversity, developer tool usage, and the presence of sensitive API calls such as CreateUser, CreateAccessKey, RunInstances, and AssumeRole.
Detects anomalous credential access behavior in Azure Key Vault where a single identity performs more than 20 secret, key, or certificate read/list operations within a 5-minute window. This behavior is indicative of potential unauthorized reconnaissance or exfiltration of secrets stored in Key Vaults, excluding known automation service principals.
Detects when a new federated identity credential is successfully added to an Azure Active Directory (Entra ID) application. This activity is a common method for attackers to establish persistent access to cloud resources by bypassing password-based authentication.
Detects changes to SharePoint tenant-level or site-level sharing policies that expand external access to 'Anyone' (anonymous links) or 'ExternalUserAndGuestSharing'. Such modifications represent a significant security posture regression that may facilitate unauthorized data access or facilitate exfiltration pathways.
Detects rapid, automated enumeration of Azure AD users, groups, and directory roles via the Microsoft Graph API immediately post-compromise. This rule identifies a high volume of queries (more than 50 within a 5-minute window) originating from a single account and IP address, targeting either 'Microsoft Graph' as the application or 'SearchQueryPerformed' as the action type.
Detects non-interactive Microsoft Graph OAuth2 token requests originating from unmanaged, deviceless sessions that falsely claim MFA satisfaction. The detection focuses on specific user agents known to be associated with automated token replay attacks and looks for multiple unique token identifiers per user session, which is indicative of credential or token theft rather than standard service account or application activity.
This rule detects Adversary-in-the-Middle (AiTM) session hijacking against Microsoft 365, specifically targeting the Tycoon 2FA phishing kit (associated with campaigns like Payroll Pirate). It correlates two distinct malicious behaviors: the initial MFA capture phase (involving specific error codes and spoofed user agents) and subsequent illicit token replay against the Microsoft Graph API from unmanaged devices.
Detects the use of the RoadTx tool to perform a Resource Owner Password Credential (ROPC) grant against Microsoft Graph while bypassing MFA. This behavior leverages CVE-2025-0309 by abusing hidden Conditional Access exclusions for specific client IDs, resulting in an authentication token issued without an MFA claim.
This rule detects suspicious activities related to AWS S3 buckets that could indicate a bucket hijacking attempt or unauthorized replication to an external account. Specifically, it looks for two scenarios: 1) an S3 bucket being deleted and then recreated by a different AWS account within a one-hour window, suggesting a namespace hijacking, or 2) an S3 bucket being deleted while a PutBucketReplication event references an external AWS account, indicating an attempt to exfiltrate data or maintain access through replication.
This rule detects a potential AWS S3 bucket name hijacking scenario. It looks for instances where an S3 bucket is deleted and then a new bucket with the exact same name is created within a short time frame (up to 1 hour) by a *different* AWS account. This pattern can be used to hijack S3 replication rule destinations, enabling silent data exfiltration to an attacker-controlled account. The rule also attempts to identify if the original bucket had replication configured.
This rule detects the creation of Temporary Access Passes (TAPs) via the Microsoft Graph API targeting highly privileged accounts. This activity could indicate an attacker abusing a service principal with UserAuthMethod-TAP.ReadWrite.All permissions to gain temporary access to critical accounts like Global Administrators, Privileged Role Administrators, or Security Administrators. The rule specifically looks for POST requests to the 'temporaryAccessPassMethods' endpoint in Microsoft Graph Activity Logs and correlates this with IdentityInfo to identify if the target user holds a privileged role.
This rule monitors the creation of new Azure Function Apps and identifies those that receive external, non-private network requests within 48 hours of their creation. This pattern may indicate the deployment of malicious or unauthorized serverless infrastructure for command-and-control, proxying, or automated tasks.
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