Rudra Verma
@RudravermaTrusted contributorCompletionist
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108 detections
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This rule detects attempts to perform a mass device wipe or deletion using Microsoft Intune. It identifies devices that have been wiped or deleted within the last 24 hours and enriches this information with device details such as name, user, OS, and ownership. This can indicate a destructive attack or an attempt to remove evidence.
This rule detects suspicious sign-in activity for a specific user principal name (UPN) within the last 7 days, immediately preceding a device wipe event. It focuses on identifying the actor's initial access or activity before initiating a mass device wipe.
This rule detects outbound network connections to a predefined list of suspicious cloud storage and file-sharing services. These services are often used by adversaries for exfiltration of collected data, providing a covert channel due to their common use and potential for SSL/TLS encryption. The rule specifically looks for `RemoteUrl` containing any of the domains listed in `suspiciousexfildomains`.
This rule detects suspicious modifications to Remote Desktop Protocol (RDP) configurations via `reg.exe` and `netsh.exe`. Specifically, it looks for attempts to enable RDP by setting `fDenyTSConnections` to 0, modify the `UserAuthentication` setting in `RDP-Tcp` to 0, or add a firewall rule to allow RDP traffic on port 3389. These actions can indicate an adversary attempting to establish or facilitate remote access to a system.
This rule detects when public or anonymous access is enabled for an Azure Storage Account. This configuration change can lead to potential data exposure, as it allows unauthenticated users to access blobs within the storage account. The rule specifically looks for 'STORAGEACCOUNTS/WRITE' or 'STORAGEACCOUNTS/BLOBSERVICES/WRITE' operations that successfully modify the storage account configuration to allow public access.
This rule detects 'impossible travel' scenarios where a user successfully signs in from two geographically distant locations within an implausibly short time frame (less than 120 minutes). It specifically looks for sign-ins where the country of origin changes between consecutive successful login events for the same user.
This rule detects successful sign-ins to Microsoft 365 services that occur via legacy authentication protocols. These protocols (e.g., Exchange ActiveSync, IMAP4, POP3, SMTP AUTH) do not support modern authentication methods like Multi-Factor Authentication (MFA) or Conditional Access policies, making them a potential bypass vector for adversaries who have compromised user credentials. The rule identifies the user, the specific legacy client application used, and provides details on the source IP address and country.
This rule detects potential C2 beaconing behavior by identifying devices that make a high number of periodic outbound connections (20 or more within an hour) to a single external IP address on common web and C2-related ports (80, 443, 8080, 8443, 4444, 5555, 8888, 9001). The rule summarizes these connections by device, remote IP, and initiating process, highlighting sustained communication patterns indicative of command and control.
This rule detects attempts to grant consent to OAuth applications, which could indicate an illicit consent grant attack. It specifically looks for successful operations related to consenting to applications, adding app role assignments to service principals, adding delegated permission grants, or adding OAuth2PermissionGrants within audit logs. The rule extracts details such as the target application, the user who consented, their initiating IP address, and the permissions granted.
This rule detects a high volume of Azure resource deletions by a single user within a short timeframe (30 minutes). This behavior is indicative of a destructive attack or wiper activity, where an adversary attempts to delete critical cloud infrastructure to disrupt operations or cause data loss. The rule specifically looks for 'delete' operations that were successful and counts them per caller and IP address, triggering an alert if the count exceeds a defined threshold.
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