Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Microsoft Defender for Identity raises alert on suspicious Kerberos ticket, pointing to a potential overpass-the-hash attack.
Once attackers gain credentials for a user with higher privileges, they will use the stolen credentials to sign into other devices and move laterally.
This query finds related sign-in events following overpass-the-hash attack to trace the footprint of the impersonated user.
Once attackers gain credentials for a user with higher privileges, they will use the stolen credentials to sign into other devices and move laterally.
This query finds related sign-in events following overpass-the-hash attack to trace the footprint of the impersonated user.
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.
// Detect Active Directory service accounts that are not active because their last logon was more than 14 days ago
// Replace XXX on line 4 with the naming convention start of your Active Directory service accounts
// Replace XXX on line 4 with the naming convention start of your Active Directory service accounts
This query looks for events that are near in time to a detected event.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
This query looks for events that are near in time to a detected event.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
This query looks for events that are near in time to a detected event.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
This query looks for events that are near in time to a detected event.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
It shows how you could avoid typing exact timestamps, and replace it with a simple query to get the timestamp of your pivot event (e.g. a detected event).
This is useful when you have queries that you run often - e.g. as part of your regular investigation of an alert.
Original query: filter for network logon events right before some timestamp.
Detects the potential use of Rubeus by identifying the registration of a new trusted logon process. This activity is often associated with Kerberos-related attacks, where Rubeus is used to manipulate Kerberos tickets or processes for privilege escalation or lateral movement.
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