The is the first blog in a series to address long term availability of advanced hunting data using the streaming API. The primary focus will be data from Microsoft Defender for Endpoint, followed up later with posts on other data tables (i.e., Microsoft Defender for Office 365).
2020 saw one of the biggest supply-chain attacks in the industry (so far) with no entity immune to its effects. Over 6 months later, organizations continue to struggle with the impact of the breach - hampered by the lack the visibility and/or the retention of that data to fully eradicate the threat.
Fast-forward to 2021, customers filled some of the visibility gap with tools like an endpoint detection and response (EDR) solution. Assuming all EDR tools are all equal (they’re not), organizations could move data into a SIEM solution to extend retention and reap the traditional rewards (i.e., correlation, workflow, etc.). While this would appear to be good on paper, the reality is that keeping data for long periods of time in the SIEM is expensive.
Are there other options? Pushing data to cold storage or cheap cloud containers/blobs is a possible remedy, however what supply chain attacks have shown us is that we need a way for data to be available for hunting – data stored using these methods often require data to be hydrated before it is usable (i.e., querying) which often comes at a high operational cost. This hydration may also come over with caveats, the most prevalent one being that restored data and current data often resides on different platforms, requiring queries/IP to be re-written.
In summary, the most ideal solution would:
Retain data for an organization’s required length of time.
Make hydration quick, simple, scalable, and/or, always online.
Reduce or eliminate the need for IP (queries, investigations, ...) to be recreated.
The solution
Azure Data Explorer (ADX) offers a scalable and cost-effective platform for security teams to build their hunting platforms on. There are many methods to bring data to ADX but this post will be focused be the event-hub which offers terrific scalability and speed. Data from Microsoft 365 Defender (M365D - security.microsoft.com), Microsoft's XDR solution, more specifically data from the EDR, Microsoft Defender For Endpoint (MDE - securitycenter.windows.com) will be sent to ADX to solve the aforementioned problems.
Solution architecture:
Using Microsoft Defender For Endpoint's streaming API to an event-hub and Azure Data Explorer, security teams can have limitless query access to their data.
Questions and considerations:
Q: Should I go from Sentinel/Azure Monitor to the event-hub (continuous export) or do I go straight to the event hub from source? A: Certainly there are benefits to bringing in EDR data to a SIEM (correlations, case management, etc.,). The method described in this post will allow data to be equally accessible, for longer periods of time, in a more cost effective manner. In addition, one could consider moving "alertable" data to the SIEM, and supporting data to ADX.
Q: Are all tables supported in continuous export? A: Not yet. The list of supported tables can be found here.
Q: How long do I need to retain information for? How big should I make the event-hub? + + + A: There are numerous resources to understand how to size and scale. Navigating through this document will help you at least understand how to bring data in so sizing can be done with the most accurate numbers.
Prior to starting, here are several “variables” which will be referred to. To eliminate effort around recreating queries, keep the table names the same.
Raw table for import: XDRRaw
Mapping for raw data: XDRRawMapping
Event-hub resource ID: <myEHRID>
Event-Hub name: <myEHName>
Table names to be created:
DeviceRegistryEvents
DeviceFileCertificateInfo
DeviceEvents
DeviceImageLoadEvents
DeviceLogonEvents
DeviceFileEvents
DeviceNetworkInfo
DeviceProcessEvents
DeviceInfo
DeviceNetworkEvents
Step 1: Create the Event-hub
For your initial event-hub, leverage the defaults and follow the basic configuration. Remember to create the event-hub and not just the namespace. Record the values as previously mentioned - Event–hub resource ID and event-hub name.
Step 2: Enable the Streaming API in Microsoft 365 Defender/Microsoft Defender for Endpoint to Send Data to the Event-hub
Using the previously noted event-hub resource ID and name and follow the documentation to get data into the event-hub. After a few moments, click on the event-hub and review the data to verify data is being transferred.
Create the event-hub namespace AND the event-hub. Record the resource ID of the namespace and name of the event-hub for use when creating the streaming API.
Step 3: Create the ADX Cluster
As with the event-hub, ADX clusters are very configurable after-the-fact and a guide is available for a simple configuration.
Step 4: Create a Data Connection to Microsoft Defender for Endpoint
Prior to creating the data connection, a staging table and mapping need to be configured. Navigate to the previously created database and select Query or from the cluster, select query, and make sure your database is highlighted.
Use the code below into the query area to create the RAW table with name XDRRaw:
//Create the staging table (use the above RAW table name)
.create table XDRRaw (Raw: dynamic)
The following will create the mapping with name XDRRawMapping:
//Pull the elements into the first column so we can parse them (use the above RAW Mapping Name)
.create table XDRRaw ingestion json mapping 'XDRRawMapping' '[{"column":"Raw","path":"$","datatype":"dynamic","transform":null}]'
With the RAW staging table and mapping function created, navigate to the database, and create a new data connection in the “Data Ingestion” setting under “Settings”. It should look as follows:
Create a data connection only after you have created the RAW table and the mapping.
NOTE: The Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API supplies multiple tables of data so using MULTILINE JSON is the data format.
If all permissions are correct, the data connection should create without issue... Congratulations! Query the RAW table to review the data sources coming in from the service with the following query:
//Here’s a list of the tables you’re going to have to migrate
XDRRaw
| mv-expand Raw.records
| project Properties=Raw_records.properties, Category=Raw_records.category
| summarize by tostring(Category)
NOTE: Be patient! ADX has a ingests in batches every 5 minutes (default) but can be configured lower however it is advised to keep the default value as lower values may result in increased latency. For more information about the batching policy, see IngestionBatching policy.
Step 4: Ingest Specified Tables
The Microsoft Defender for Endpoint data stream enables teams to pick one, some, or all tables to be exported. Copy and run the queries below (one at a time in each code block) based on which tables are being pushed to the event-hub.
With data flowing through, select any device query from the security.microsoft.com/securitycenter.windows.com portal and run it, “word for word” in the ADX portal. As an example, the following query shows devices creating a PNP device call:
In addition to being to reuse queries, if you are also using Azure Sentinel and have Microsoft 365 Defender/Microsoft Defender for Endpoint data connected, try the following:
Navigate to your ADX cluster and get copy the scope. It will be formatted as <clusterName>.<region>/<databaseName>:
Retrieve the ADX scope for external use from Azure Sentinel.NOTE: Unlike queries in Microsoft 365 Defender/Microsoft Defender for Endpoint and Sentinel/Log Analytics, queries in ADX do NOT have a default time filter. Queries run without filters will query the entire database and likely impact performance.
Navigate to an Azure Sentinel instance and place the query together with the adx() operator:
NOTE: As the ADX operator is external, auto-complete will not work.
Notice the query will complete completely but not with Azure Sentinel resources but rather the resources in ADX! (This operator is not available in Analytics rules though)
Summary
Using the Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API and Azure Data Explorer (ADX), teams can very easily achieve terrific scalability on long term, investigative hunting, and forensics. Cost continues to be another key benefit as well as the ability to reuse IP/queries.
For organizations looking to expand their EDR signal and do auto correlation with 3rd party data sources, consider leveraging Azure Sentinel, where there are a number of 1st and 3rd party data connectors which enable rich context to added to existing Microsoft 365 Defender/Microsoft Defender for Endpoint data. An example of these enhancements can be found at https://aka.ms/SentinelFusion.
It is quite an extensive process. I understand that it is copying and pasting. I suggest making it a bit simpler (GUI ?)
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Leverage the power of Azure Data Explorer (ADX) to extend your Microsoft 365 Defender (XDR) / Microsoft Defender For Endpoint advanced hunting data for as long as you want (10 years!). If you enjoy rewriting queries just to look through old data and spending time and money rehydrating it, this post isn't for you!
","body":"
The is the first blog in a series to address long term availability of advanced hunting data using the streaming API. The primary focus will be data from Microsoft Defender for Endpoint, followed up later with posts on other data tables (i.e., Microsoft Defender for Office 365).
\n
\n
2020 saw one of the biggest supply-chain attacks in the industry (so far) with no entity immune to its effects. Over 6 months later, organizations continue to struggle with the impact of the breach - hampered by the lack the visibility and/or the retention of that data to fully eradicate the threat.
\n
\n
Fast-forward to 2021, customers filled some of the visibility gap with tools like an endpoint detection and response (EDR) solution. Assuming all EDR tools are all equal (they’re not), organizations could move data into a SIEM solution to extend retention and reap the traditional rewards (i.e., correlation, workflow, etc.). While this would appear to be good on paper, the reality is that keeping data for long periods of time in the SIEM is expensive.
\n
\n
Are there other options? Pushing data to cold storage or cheap cloud containers/blobs is a possible remedy, however what supply chain attacks have shown us is that we need a way for data to be available for hunting – data stored using these methods often require data to be hydrated before it is usable (i.e., querying) which often comes at a high operational cost. This hydration may also come over with caveats, the most prevalent one being that restored data and current data often resides on different platforms, requiring queries/IP to be re-written.
\n
\n
In summary, the most ideal solution would:
\n\n
Retain data for an organization’s required length of time.
\n
Make hydration quick, simple, scalable, and/or, always online.
\n
Reduce or eliminate the need for IP (queries, investigations, ...) to be recreated.
\n\n
\n
The solution
\n
Azure Data Explorer (ADX) offers a scalable and cost-effective platform for security teams to build their hunting platforms on. There are many methods to bring data to ADX but this post will be focused be the event-hub which offers terrific scalability and speed. Data from Microsoft 365 Defender (M365D - security.microsoft.com), Microsoft's XDR solution, more specifically data from the EDR, Microsoft Defender For Endpoint (MDE - securitycenter.windows.com) will be sent to ADX to solve the aforementioned problems.
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\n
Solution architecture:
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\n
Using Microsoft Defender For Endpoint's streaming API to an event-hub and Azure Data Explorer, security teams can have limitless query access to their data.
\n
Questions and considerations:
\n
\n
Q: Should I go from Sentinel/Azure Monitor to the event-hub (continuous export) or do I go straight to the event hub from source? A: Certainly there are benefits to bringing in EDR data to a SIEM (correlations, case management, etc.,). The method described in this post will allow data to be equally accessible, for longer periods of time, in a more cost effective manner. In addition, one could consider moving \"alertable\" data to the SIEM, and supporting data to ADX.
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Q: Are all tables supported in continuous export? A: Not yet. The list of supported tables can be found here.
\n
Q: How long do I need to retain information for? How big should I make the event-hub? + + + A: There are numerous resources to understand how to size and scale. Navigating through this document will help you at least understand how to bring data in so sizing can be done with the most accurate numbers.
\n
\n
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Prior to starting, here are several “variables” which will be referred to. To eliminate effort around recreating queries, keep the table names the same.
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\n
Raw table for import: XDRRaw
\n
Mapping for raw data: XDRRawMapping
\n
Event-hub resource ID: <myEHRID>
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Event-Hub name: <myEHName>
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Table names to be created:\n
\n
DeviceRegistryEvents
\n
DeviceFileCertificateInfo
\n
DeviceEvents
\n
DeviceImageLoadEvents
\n
DeviceLogonEvents
\n
DeviceFileEvents
\n
DeviceNetworkInfo
\n
DeviceProcessEvents
\n
DeviceInfo
\n
DeviceNetworkEvents
\n
\n
\n
\n
Step 1: Create the Event-hub
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For your initial event-hub, leverage the defaults and follow the basic configuration. Remember to create the event-hub and not just the namespace. Record the values as previously mentioned - Event–hub resource ID and event-hub name.
\n
\n
Step 2: Enable the Streaming API in Microsoft 365 Defender/Microsoft Defender for Endpoint to Send Data to the Event-hub
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Using the previously noted event-hub resource ID and name and follow the documentation to get data into the event-hub. After a few moments, click on the event-hub and review the data to verify data is being transferred.
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Create the event-hub namespace AND the event-hub. Record the resource ID of the namespace and name of the event-hub for use when creating the streaming API.
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Step 3: Create the ADX Cluster
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As with the event-hub, ADX clusters are very configurable after-the-fact and a guide is available for a simple configuration.
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\n
Step 4: Create a Data Connection to Microsoft Defender for Endpoint
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Prior to creating the data connection, a staging table and mapping need to be configured. Navigate to the previously created database and select Query or from the cluster, select query, and make sure your database is highlighted.
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\n
Use the code below into the query area to create the RAW table with name XDRRaw:
\n
\n
\n
//Create the staging table (use the above RAW table name)\n.create table XDRRaw (Raw: dynamic)\n
\n
\n
\n
The following will create the mapping with name XDRRawMapping:
\n
\n
\n
//Pull the elements into the first column so we can parse them (use the above RAW Mapping Name)\n.create table XDRRaw ingestion json mapping 'XDRRawMapping' '[{\"column\":\"Raw\",\"path\":\"$\",\"datatype\":\"dynamic\",\"transform\":null}]'\n
\n
\n
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With the RAW staging table and mapping function created, navigate to the database, and create a new data connection in the “Data Ingestion” setting under “Settings”. It should look as follows:
\n
\n
Create a data connection only after you have created the RAW table and the mapping.
\n
NOTE: The Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API supplies multiple tables of data so using MULTILINE JSON is the data format.
\n
\n
If all permissions are correct, the data connection should create without issue... Congratulations! Query the RAW table to review the data sources coming in from the service with the following query:
\n
\n
\n
//Here’s a list of the tables you’re going to have to migrate \nXDRRaw\n| mv-expand Raw.records\n| project Properties=Raw_records.properties, Category=Raw_records.category\n| summarize by tostring(Category)
\n
\n
\n
NOTE: Be patient! ADX has a ingests in batches every 5 minutes (default) but can be configured lower however it is advised to keep the default value as lower values may result in increased latency. For more information about the batching policy, see IngestionBatching policy.
\n
\n
Step 4: Ingest Specified Tables
\n
The Microsoft Defender for Endpoint data stream enables teams to pick one, some, or all tables to be exported. Copy and run the queries below (one at a time in each code block) based on which tables are being pushed to the event-hub.
With data flowing through, select any device query from the security.microsoft.com/securitycenter.windows.com portal and run it, “word for word” in the ADX portal. As an example, the following query shows devices creating a PNP device call:
In addition to being to reuse queries, if you are also using Azure Sentinel and have Microsoft 365 Defender/Microsoft Defender for Endpoint data connected, try the following:
\n\n
Navigate to your ADX cluster and get copy the scope. It will be formatted as <clusterName>.<region>/<databaseName>:
Retrieve the ADX scope for external use from Azure Sentinel.NOTE: Unlike queries in Microsoft 365 Defender/Microsoft Defender for Endpoint and Sentinel/Log Analytics, queries in ADX do NOT have a default time filter. Queries run without filters will query the entire database and likely impact performance.
\n
Navigate to an Azure Sentinel instance and place the query together with the adx() operator:
NOTE: As the ADX operator is external, auto-complete will not work.
\n
\n\n
Notice the query will complete completely but not with Azure Sentinel resources but rather the resources in ADX! (This operator is not available in Analytics rules though)
\n
\n
Summary
\n
Using the Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API and Azure Data Explorer (ADX), teams can very easily achieve terrific scalability on long term, investigative hunting, and forensics. Cost continues to be another key benefit as well as the ability to reuse IP/queries.
\n
\n
For organizations looking to expand their EDR signal and do auto correlation with 3rd party data sources, consider leveraging Azure Sentinel, where there are a number of 1st and 3rd party data connectors which enable rich context to added to existing Microsoft 365 Defender/Microsoft Defender for Endpoint data. An example of these enhancements can be found at https://aka.ms/SentinelFusion.
The is the first blog in a series to address long term availability of advanced hunting data using the streaming API. The primary focus will be data from Microsoft Defender for Endpoint, followed up later with posts on other data tables (i.e., Microsoft Defender for Office 365).
\n
\n
2020 saw one of the biggest supply-chain attacks in the industry (so far) with no entity immune to its effects. Over 6 months later, organizations continue to struggle with the impact of the breach - hampered by the lack the visibility and/or the retention of that data to fully eradicate the threat.
\n
\n
Fast-forward to 2021, customers filled some of the visibility gap with tools like an endpoint detection and response (EDR) solution. Assuming all EDR tools are all equal (they’re not), organizations could move data into a SIEM solution to extend retention and reap the traditional rewards (i.e., correlation, workflow, etc.). While this would appear to be good on paper, the reality is that keeping data for long periods of time in the SIEM is expensive.
\n
\n
Are there other options? Pushing data to cold storage or cheap cloud containers/blobs is a possible remedy, however what supply chain attacks have shown us is that we need a way for data to be available for hunting – data stored using these methods often require data to be hydrated before it is usable (i.e., querying) which often comes at a high operational cost. This hydration may also come over with caveats, the most prevalent one being that restored data and current data often resides on different platforms, requiring queries/IP to be re-written.
\n
\n
In summary, the most ideal solution would:
\n\n
Retain data for an organization’s required length of time.
\n
Make hydration quick, simple, scalable, and/or, always online.
\n
Reduce or eliminate the need for IP (queries, investigations, ...) to be recreated.
\n\n
\n
The solution
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Azure Data Explorer (ADX) offers a scalable and cost-effective platform for security teams to build their hunting platforms on. There are many methods to bring data to ADX but this post will be focused be the event-hub which offers terrific scalability and speed. Data from Microsoft 365 Defender (M365D - security.microsoft.com), Microsoft's XDR solution, more specifically data from the EDR, Microsoft Defender For Endpoint (MDE - securitycenter.windows.com) will be sent to ADX to solve the aforementioned problems.
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Solution architecture:
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Using Microsoft Defender For Endpoint's streaming API to an event-hub and Azure Data Explorer, security teams can have limitless query access to their data.
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Questions and considerations:
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Q: Should I go from Sentinel/Azure Monitor to the event-hub (continuous export) or do I go straight to the event hub from source? A: Certainly there are benefits to bringing in EDR data to a SIEM (correlations, case management, etc.,). The method described in this post will allow data to be equally accessible, for longer periods of time, in a more cost effective manner. In addition, one could consider moving \"alertable\" data to the SIEM, and supporting data to ADX.
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Q: Are all tables supported in continuous export? A: Not yet. The list of supported tables can be found here.
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Q: How long do I need to retain information for? How big should I make the event-hub? + + + A: There are numerous resources to understand how to size and scale. Navigating through this document will help you at least understand how to bring data in so sizing can be done with the most accurate numbers.
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Prior to starting, here are several “variables” which will be referred to. To eliminate effort around recreating queries, keep the table names the same.
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Raw table for import: XDRRaw
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Mapping for raw data: XDRRawMapping
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Event-hub resource ID: <myEHRID>
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Event-Hub name: <myEHName>
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Table names to be created:\n
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DeviceRegistryEvents
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DeviceFileCertificateInfo
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DeviceEvents
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DeviceImageLoadEvents
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DeviceLogonEvents
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DeviceFileEvents
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DeviceNetworkInfo
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DeviceProcessEvents
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DeviceInfo
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DeviceNetworkEvents
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Step 1: Create the Event-hub
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For your initial event-hub, leverage the defaults and follow the basic configuration. Remember to create the event-hub and not just the namespace. Record the values as previously mentioned - Event–hub resource ID and event-hub name.
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Step 2: Enable the Streaming API in Microsoft 365 Defender/Microsoft Defender for Endpoint to Send Data to the Event-hub
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Using the previously noted event-hub resource ID and name and follow the documentation to get data into the event-hub. After a few moments, click on the event-hub and review the data to verify data is being transferred.
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Create the event-hub namespace AND the event-hub. Record the resource ID of the namespace and name of the event-hub for use when creating the streaming API.
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Step 3: Create the ADX Cluster
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As with the event-hub, ADX clusters are very configurable after-the-fact and a guide is available for a simple configuration.
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Step 4: Create a Data Connection to Microsoft Defender for Endpoint
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Prior to creating the data connection, a staging table and mapping need to be configured. Navigate to the previously created database and select Query or from the cluster, select query, and make sure your database is highlighted.
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Use the code below into the query area to create the RAW table with name XDRRaw:
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\n//Create the staging table (use the above RAW table name)\n.create table XDRRaw (Raw: dynamic)\n\n
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The following will create the mapping with name XDRRawMapping:
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\n//Pull the elements into the first column so we can parse them (use the above RAW Mapping Name)\n.create table XDRRaw ingestion json mapping 'XDRRawMapping' '[{\"column\":\"Raw\",\"path\":\"$\",\"datatype\":\"dynamic\",\"transform\":null}]'\n\n
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With the RAW staging table and mapping function created, navigate to the database, and create a new data connection in the “Data Ingestion” setting under “Settings”. It should look as follows:
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Create a data connection only after you have created the RAW table and the mapping.
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NOTE: The Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API supplies multiple tables of data so using MULTILINE JSON is the data format.
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If all permissions are correct, the data connection should create without issue... Congratulations! Query the RAW table to review the data sources coming in from the service with the following query:
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\n//Here’s a list of the tables you’re going to have to migrate \nXDRRaw\n| mv-expand Raw.records\n| project Properties=Raw_records.properties, Category=Raw_records.category\n| summarize by tostring(Category)\n
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NOTE: Be patient! ADX has a ingests in batches every 5 minutes (default) but can be configured lower however it is advised to keep the default value as lower values may result in increased latency. For more information about the batching policy, see IngestionBatching policy.
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Step 4: Ingest Specified Tables
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The Microsoft Defender for Endpoint data stream enables teams to pick one, some, or all tables to be exported. Copy and run the queries below (one at a time in each code block) based on which tables are being pushed to the event-hub.
With data flowing through, select any device query from the security.microsoft.com/securitycenter.windows.com portal and run it, “word for word” in the ADX portal. As an example, the following query shows devices creating a PNP device call:
In addition to being to reuse queries, if you are also using Azure Sentinel and have Microsoft 365 Defender/Microsoft Defender for Endpoint data connected, try the following:
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Navigate to your ADX cluster and get copy the scope. It will be formatted as <clusterName>.<region>/<databaseName>:
Retrieve the ADX scope for external use from Azure Sentinel.NOTE: Unlike queries in Microsoft 365 Defender/Microsoft Defender for Endpoint and Sentinel/Log Analytics, queries in ADX do NOT have a default time filter. Queries run without filters will query the entire database and likely impact performance.
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Navigate to an Azure Sentinel instance and place the query together with the adx() operator: adx(\"###ADXSCOPE###\").DeviceEvents\n| where ActionType == \"PnpDeviceConnected\"\n| extend parsed=parse_json(AdditionalFields)\n| project className=parsed.ClassName, description=parsed.DeviceDescription, parsed.DeviceId, DeviceName\nFor example:
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NOTE: As the ADX operator is external, auto-complete will not work.
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Notice the query will complete completely but not with Azure Sentinel resources but rather the resources in ADX! (This operator is not available in Analytics rules though)
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Summary
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Using the Microsoft 365 Defender/Microsoft Defender for Endpoint streaming API and Azure Data Explorer (ADX), teams can very easily achieve terrific scalability on long term, investigative hunting, and forensics. Cost continues to be another key benefit as well as the ability to reuse IP/queries.
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For organizations looking to expand their EDR signal and do auto correlation with 3rd party data sources, consider leveraging Azure Sentinel, where there are a number of 1st and 3rd party data connectors which enable rich context to added to existing Microsoft 365 Defender/Microsoft Defender for Endpoint data. An example of these enhancements can be found at https://aka.ms/SentinelFusion.
Special thanks to , , , , , and for their insights and time into this post.
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Leverage the power of Azure Data Explorer (ADX) to extend your Microsoft 365 Defender (XDR) / Microsoft Defender For Endpoint advanced hunting data for as long as you want (10 years!). If you enjoy rewriting queries just to look through old data and spending time and money rehydrating it, this post isn't for you!
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is there any third party integration that allow us to create alerting based a schedule custom hunting queries against Azure Data Explorer's data?
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This is awesome. Really look forward to the the article on Defender for O365.
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It is quite an extensive process. I understand that it is copying and pasting. I suggest making it a bit simpler (GUI ?)
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