Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects an account performing multiple interactive logons (LogonType 2) from at least 3 unique IP addresses within a 5-minute window. This behavior can indicate credential compromise or an adversary attempting to move laterally or access multiple systems using stolen credentials.
This rule detects when a single user principal name (UPN) attempts five or more sign-ins from the same IP address within a one-hour window, and each sign-in is flagged with a 'RiskDetail' other than 'none' but still results in a 'Success' status. This could indicate an attacker attempting to bypass security controls or an account compromise where the attacker is repeatedly trying to access the account from a consistent location, possibly with different credentials or methods, until successful.
Detects successful or anomalous authentications utilizing the Microsoft device code flow. Kali365 and other phishing-as-a-service platforms actively abuse this flow to register attacker devices, bypassing multi-factor authentication (MFA) and gaining unauthorized access to Microsoft 365 environments.
This rule detects an unusual number of local or remote interactive logons (LogonType 2 or 10) by the 'SYSTEM' account within a one-hour window. While the SYSTEM account is legitimate, direct interactive logons are rare and multiple occurrences could indicate an attempt to escalate privileges or maintain persistence by an attacker.
This rule detects potential Pass-the-Hash (PtH) attacks by looking for multiple successful network logons (LogonType 3) using NTLM authentication for the same user from the same IP address. A count of 5 or more such events is considered suspicious.
This rule correlates successful VPN authentication events with the subsequent execution of tools commonly associated with ransomware staging activities within a 6-hour window. It aims to detect initial access via VPN followed by preparatory actions for ransomware deployment. The rule specifically looks for VPN logins from 'Check Point' devices and process executions of 'rclone.exe', '7z.exe', 'powershell.exe', 'wevtutil.exe', 'vssadmin.exe', or 'nltest.exe'.
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
This rule detects a pattern indicative of password spraying or brute force attacks against user accounts. It identifies instances where a single user principal name (UPN) and IP address combination has at least 5 failed sign-in attempts and at least 1 successful sign-in attempt within a 30-minute window. This combination of failed and successful logins from the same source for the same user suggests an attacker successfully guessed a password after multiple attempts, or a password spraying attack where one of the sprayed passwords was correct.
This rule detects an unusually high volume of logon events (both successful and failed) or a large number of unique users attempting to log on within a 5-minute window. This behavior is indicative of potential brute-force attacks or credential stuffing attempts against Windows systems.
This rule detects potential Golden Ticket attacks by looking for multiple successful Kerberos authentication events (EventID 4624) with LogonType 3 (network logon) and a specific TicketEncryptionType (0x17), originating from the same IP address and targeting the same user, within a short timeframe and with a long ticket lifetime. A Golden Ticket attack involves an adversary forging Kerberos Ticket Granting Tickets (TGTs) to gain unauthorized access to resources.
This rule detects a high volume of successful sign-in attempts to Exchange Online from a single IP address where the UserPrincipalName ends with '@' (indicating an anonymous or malformed UPN) and Conditional Access was not applied. This pattern can be indicative of anonymous SMTP relay abuse, often used for spamming or phishing campaigns.
This rule detects the issuance of OAuth tokens or OAuth consent events within cloud applications. It specifically looks for these events where the client application is not 'Microsoft Teams' or 'Azure CLI'. The rule summarizes the number of grants and distinct users for each client application and token ID over hourly intervals. This can help identify potentially unauthorized or suspicious OAuth application consents.
This rule detects an unusually high volume (5 or more within an hour) of successful logons by 'SYSTEM' or 'LOCAL SERVICE' accounts. While these are legitimate system accounts, a sudden surge in their logon activity could indicate unusual system behavior, potential compromise, or misconfiguration leading to excessive system account usage.
Detects potential session replay attacks indicative of Kali365 and other AitM (Adversary-in-the-Middle) proxying phishing kits. This rule isolates successful user logins containing a SessionId. To fully operationalize this for AitM detection, defenders must utilize SIEM-based correlation (e.g., statistical or window-based queries) to track a single SessionId originating from multiple geographically disparate IP addresses within a short timeframe.
This rule detects when a single account initiates 5 or more successful Remote Desktop Protocol (RDP) connections within a one-hour window. This behavior can be indicative of an adversary attempting to gain widespread access within a network, potentially through credential stuffing, brute-force attacks, or lateral movement using compromised credentials.
This rule detects potential Golden Ticket attacks by looking for multiple successful Kerberos authentication events (EventID 4624) with LogonType 3 (network logon) and a specific TicketEncryptionType (0x17), originating from the same IP address and targeting the same user, within a short timeframe and with a long ticket lifetime. A Golden Ticket attack involves an adversary forging Kerberos Ticket Granting Tickets (TGTs) to gain unauthorized access to resources.
This rule detects suspicious activity where a user successfully performs a multi-factor authentication (MFA) device login to Microsoft Office 365 via a browser, and within a 15-minute window, the same user either creates a new inbox rule or adds a new device. This combination of events could indicate an adversary gaining initial access and then setting up persistence (e.g., forwarding emails) or further device enrollment.
This rule detects an account performing multiple interactive logons (LogonType 2) from at least 3 unique IP addresses within a 5-minute window. This behavior can indicate credential compromise or an adversary attempting to move laterally or access multiple systems using stolen credentials.
This rule identifies successful device code authentications using the Microsoft Authentication Broker application (AppId '29d9ed98-a469-4536-ade2-f981bc1d605e') targeting Microsoft Graph (ResourceIdentity '00000003-0000-0000-c000-000000000000'). It specifically looks for these authentications originating from untrusted network locations. This activity is highly anomalous and can indicate an attacker generating Primary Refresh Tokens (PRTs) via device code phishing.
This rule detects unusual logon activity for service accounts. It identifies service accounts by looking for a dollar sign ($) at the end of the username. The rule then counts logons, unique IP addresses, and unique computers for these service accounts within one-hour bins. An alert is triggered if a service account has 10 or more logons or logs in from 5 or more unique IP addresses within that hour, indicating potential abuse or compromise.
Detects successful device code flow sign-ins to the Microsoft Authentication Broker application targeting the Microsoft Graph resource, specifically when the sign-in does not originate from a trusted named location. This activity can indicate a device code phishing attempt where an attacker tricks a user into authenticating a malicious application.
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