Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects attempts to abuse the device code flow targeting Microsoft Office and Authentication Broker applications from unmanaged and non-compliant devices with unbound tokens. This activity is indicative of device code phishing, where an attacker tricks a user into authenticating a malicious application.
Okta MFA Push Bombing / Fatigue
Cortex XDR
Detects repeated push denials for the same user within a short timeframe, indicating an active MFA fatigue attack where an adversary is attempting to overwhelm a user with MFA requests in hopes they will eventually approve one.
This rule detects multiple failed sign-in attempts using the 'Device Code' authentication flow from various IP addresses or locations for a single user. This behavior can indicate an adversary attempting to bypass multi-factor authentication (MFA) or gain unauthorized access through device code phishing or brute-force attacks against the device code flow. The rule specifically looks for more than 3 attempts from more than 2 distinct IP addresses or locations, targeting common Microsoft applications like Office, Teams, Azure Portal, or Graph.
This rule detects potential MFA bypass attempts by identifying multiple successful sign-ins from the same user within an hour where Conditional Access policies were not applied, and no MFA method was used. This could indicate an adversary circumventing security controls to gain unauthorized access.
This rule detects an unusual pattern of multiple login attempts from several unique devices using Windows Hello for Business within a short timeframe (5 minutes) for a single user. This could indicate an MFA bypass attempt or a compromised account where an adversary is attempting to gain access from various devices.
This rule detects a potential MFA SMS code request flooding attack. It triggers when a single source IP address makes 10 or more HTTP requests containing the string "send_code" in the URI within a 60-second window. This behavior is indicative of an attacker repeatedly attempting to request MFA codes, likely in an attempt to overwhelm the user or the system, or to facilitate a SIM-swapping attack.
Detects potential multi-factor authentication (MFA) fatigue attacks in Azure AD by identifying a high number of push notification MFA challenges for a single user from a specific IP address within a short time frame. Specifically, it looks for 15 or more push notification MFA challenges within a 30-minute window.
Detects potential multi-factor authentication (MFA) fatigue attacks in Azure AD by identifying a high number of push notification MFA challenges for a single user from a specific IP address within a short time frame. Specifically, it looks for 15 or more push notification MFA challenges within a 30-minute window.
This rule detects automated multi-factor authentication (MFA) push bombing attempts targeting Duo Security's API. It specifically looks for HTTP POST requests to 'api.duosecurity.com' and triggers an alert if 10 such requests are observed from the same source IP within a 30-second window. This behavior is indicative of an attacker repeatedly sending MFA push notifications to a user's device in an attempt to overwhelm them or trick them into approving a fraudulent login.
This rule detects a potential MFA fatigue attack by monitoring repeated HTTP requests to known MFA provider domains (duo.com, okta.com, microsoft.com) containing the string "auth" in the URI. A threshold of 20 requests within 60 seconds from the same destination IP address triggers the alert, indicating an attacker might be repeatedly sending push notifications to a user's device to overwhelm them into accepting an authentication request.
This rule detects a suspicious sequence of events in Okta that could indicate a help-desk social engineering attack or account takeover. Specifically, it looks for a user's password being reset, followed by the enrollment of a new MFA factor or device for that same user, all occurring within a short time frame (1 hour) and potentially from distinct session IDs or device hashes. This pattern suggests an attacker has gained initial access (e.g., via social engineering the help desk) and is immediately attempting to establish persistence by enrolling their own MFA device.
This rule detects suspicious multi-factor authentication (MFA) behavior by identifying MFA denials that occur from an unknown IP address or with an unusual authentication method for a given user. It establishes a baseline of known IP addresses and usual authentication methods for each user over a 30-day period. Alerts are generated for recent MFA denials (within the last hour) if they involve a high-risk denial detail (e.g., too many invalid codes, user blocked) combined with an unknown IP or unusual authentication method, or if they involve any other denial reason combined with both an unknown IP and an unusual authentication method. This helps to identify potential MFA fatigue attacks or attempts to bypass MFA.
Kali365 PHaaS Device Code Detection
Cortex XDR
This rule detects potential device code phishing attempts by correlating a device code flow initiated from an unmanaged/non-compliant device with a suspicious user agent (e.g., 'python-requests' or '-live') and an 'unbound' signInTokenProtectionStatus, with a subsequent 'Cmsi:Cmsi' token replay event for the same user. This combination suggests a successful device code phishing attack where an adversary has obtained and is replaying a token after the victim has authenticated.
Identifies user login with multifactor authentication failures, which might be an indication an attacker has the password for the account but can't pass the MFA challenge.
User has indicated they haven't instigated the MFA prompt and could indicate an attacker has the password for the account.
Detects multiple multi-factor authentication (MFA) attempts that are denied or ignored by a user beyond a defined threshold within a specific lookback window. This behavior is indicative of an MFA fatigue attack, where an adversary repeatedly sends MFA requests to a user in hopes they will eventually approve one to stop the annoyance.
This rule detects multiple failed sign-in attempts using the 'Device Code' authentication flow from various IP addresses or locations for a single user. This behavior can indicate an adversary attempting to bypass multi-factor authentication (MFA) or gain unauthorized access through device code phishing or brute-force attacks against the device code flow. The rule specifically looks for more than 3 attempts from more than 2 distinct IP addresses or locations, targeting common Microsoft applications like Office, Teams, Azure Portal, or Graph.
Duo User Marked Fraud
YARA-L
This rule detects when a user marks an authentication request as fraudulent within Duo Security. This indicates a potential attempt to gain unauthorized access to a user's account, possibly through MFA fatigue or other social engineering tactics. The rule specifically looks for 'user_marked_fraud' in the security result summary of Duo authentication events.
This rule detects potential device code phishing attempts where a user accesses a commonly abused Platform-as-a-Service (PaaS) platform (Cloudflare Workers, Vercel, Amplify) and subsequently attempts to log in via the Microsoft device login endpoint within a 5-minute window. This sequence of events is indicative of an adversary luring a user to a malicious site hosted on a PaaS platform to capture a device code, which is then used to authenticate to Microsoft services.
This rule detects potential MFA push fatigue attacks by identifying a high volume of failed multi-factor authentication challenges for a single user within a short time window. It aggregates sign-in logs, specifically looking for result types indicative of MFA failures, and alerts if a user receives more than a defined threshold of MFA challenges within a 30-minute period.
This rule detects suspicious activity where an 'unfamiliar sign-in properties' alert occurs shortly after an administrator has changed a user's Multi-Factor Authentication (MFA) method. It correlates security alerts for unfamiliar sign-ins with audit logs indicating MFA method changes for the same user within a short timeframe. The rule then checks if the user's sign-in activity shows multiple IP addresses or locations, indicating a potential compromise or MFA bypass after the change.
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