Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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'This query looks for unfamiliar Sign-in's thats not seen recently for the given user
with azure portal login attempts and audit logs to help detect and reduce the analysis timeline for defenders'
with azure portal login attempts and audit logs to help detect and reduce the analysis timeline for defenders'
'This query searches for failed attempts to log in from more than 15 various users within a 5 minute timeframe from the same source. This is a potential indication of a password spray attack
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimAuthentication)'
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimAuthentication)'
'Any Alerts that fired related to a given IpAddress during the range of +6h and -3d'
'Identifies sign-in anomalies from an IP in the last hour, targeting multiple users where the password is correct after multiple attempts'
'This hunting query looks for users who have multiple failed queries in a short space of time.'
'Identifies a list of IP addresses with a minimum number (default of 5) of failed logon attempts to AWS Console.
Uses that list to identify any successful Microsoft Entra ID logons from these IPs within the same timeframe.'
Uses that list to identify any successful Microsoft Entra ID logons from these IPs within the same timeframe.'
'Identifies accounts that have been locked out by smart lockout policies. Review this results for patterns that might suggest that a password spray is triggering these smart lockout events.
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-failed-unusual-sign-ins'
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-failed-unusual-sign-ins'
'Identifies when a user account is enabled and then disabled within 10 minutes. This can be an indication of compromise and an adversary attempting to hide in the noise.'
'Identifies a list of IP addresses with a minimum number (defualt of 5) of failed logon attempts to Microsoft Entra ID.
Uses that list to identify any successful AWS Console logons from these IPs within the same timeframe.'
Uses that list to identify any successful AWS Console logons from these IPs within the same timeframe.'
'Access attempts to Azure Portal from an unauthorized user. Either invalid password or the user account does not exist.'
Query #1: Look for public IP addresses that failed to logon to a computer multiple times, using multiple accounts, and eventually succeeded.
MFA Spamming
KQL
'Identifies list of user impacted by MFA Spamming within a given time window,Default Failure count is 10 with default Time Window is 5 minutes'
'This hunting query will identify instances where a single user account has seen a high incidence of failed attempts from highly volatile IP addresses
Changing IP address for every password attempt is becoming a more common technique amongst sophisticated threat groups. Often threat groups will randomise
the user agent they are using as well as IP address. This technique has been enabled by the emergence of services providing huge numbers of residential IP
addresses. These services are often enabled through malicious browser plugins. This query is best executed over longer timeframes.
Reduce the timeRange if you have too much data. Results with the highest "IPs", "Failures" and "DaysWithAttempts" are good candidates for further
investigation. This query intentionally does not cluster on UserAgent, IP etc. This query is clustering on the highly volatile IP behaviour.'
Changing IP address for every password attempt is becoming a more common technique amongst sophisticated threat groups. Often threat groups will randomise
the user agent they are using as well as IP address. This technique has been enabled by the emergence of services providing huge numbers of residential IP
addresses. These services are often enabled through malicious browser plugins. This query is best executed over longer timeframes.
Reduce the timeRange if you have too much data. Results with the highest "IPs", "Failures" and "DaysWithAttempts" are good candidates for further
investigation. This query intentionally does not cluster on UserAgent, IP etc. This query is clustering on the highly volatile IP behaviour.'
'Identifies anomolies in signin events based on the volume of signin events over time. Use this to identify suspicious authentication patterns such as spikes in activity or out of hours events.
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-privileged-accounts#things-to-monitor'
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-privileged-accounts#things-to-monitor'
'Identifies spikes in failed sign-in events based on the volume of failed sign-in events over time. Use to identify patterns of suspicious behavior such as unusually high failed sign-in attempts from certain users.
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts'
Ref : https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts'
'Identifies an interrupted sign-in session from a country the user has not sign-in before in the last 7 days, where the password was correct. Although the session is interrupted by other controls such as multi factor authentication or conditional access policies, the user credentials should be reset due to logs indicating a correct password was observed during sign-in.'
Intent:
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
'Query shows 1200+ failed attempts by cIP per hour on server, then successful logon. Only includes > 1 user agent string or port. Could indicate successful probing and brute force success on IIS servers.'
'Detects when a privileged user account successfully authenticates from to another Microsoft Entra ID Tenant.
Authentication attempts should be investigated to ensure the activity was legitimate and if there is other similar activity.
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-successful-unusual-sign-ins'
Authentication attempts should be investigated to ensure the activity was legitimate and if there is other similar activity.
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-successful-unusual-sign-ins'
'This identifies failed logon attempts using permutations based on known first and last names within 10m time windows. Iteration through separators or order changes in the logon name may indicate potential Brute Force logon attempts.'
'An account could be blocked/locked out due to multiple reasons. This hunting query summarize blocked/lockout accounts and checks if most recent signin events for them is after last blocked accounts
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-successful-unusual-sign-ins'
Ref: https://docs.microsoft.com/azure/active-directory/fundamentals/security-operations-user-accounts#monitoring-for-successful-unusual-sign-ins'
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