NRT Rules are hard-coded to run once every minute and capture events ingested in the preceding minute.
This is for faster detection and response opportunity.
No more than 20 rules can be defined per customer at this time
As this type of rule is new, its syntax is currently limited but will gradually evolve. Therefore, at this time the following restrictions are in effect:
The query defined in an NRT rule can reference only one table. Queries can, however, refer to multiple watchlists and to threat intelligence feeds.
You cannot use unions or joins.
Because this rule type is in near real time, we have reduced the built-in delay to a minimum (two minutes).
Since NRT rules use the ingestion time rather than the event generation time (represented by the TimeGenerated field), you can safely ignore the data source delay and the ingestion time latency (see above).
Queries can run only within a single workspace. There is no cross-workspace capability.
There is no event grouping. NRT rules produce a single alert that groups all the applicable events.
For further information about Near-Real-Time, NRT, analytic rules, please visit:
During Ignite, Microsoft has announced a new set of features in the Advanced Hunting in Microsoft 365 Defender.
These features will definitely help you in the Threat Hunting process and also reduce the gap between analysts, responders and threat hunters and simplify the life of a threat hunter.
When having hunting training classes, I usually recommend to use multiple browser tabs. One for the query development, and one used to go back to previous queries to see how some things were done earlier.
for example, if you are developing a hunting query and need an if statement, external data, regex or other more advanced features it is easier to just open a previous query to see how it was solved last time. At least until you get more fluent in KQL. This is to avoid having to save your new query, go back to the old one, and then back to the new again
With the multi-tab support we can open the query in a new tab
The new Hunting Page will now provide the resource usage for the query both timing and an indicator of the resource usage
If you would like to learn more about how to optimize queries, please visit:
Schema, Functions, Queries and Detection Rules have been separated into tabs for, according to my opinion, easier access and pivoting which will give a better overview in each tab.
The schema reference will open as a side pane
When looking at one of the *events tables, the ActionType column is very useful to see which events are being logged. Earlier, I usually selected distinct ActionType in the query to have a look at the events being logged. Now, it’s possible to use the quick access from the portal to expand all action types for a specific table.
Above image shows the action types for DeviceFileEvents. In the DeviceEvents there are around 180 different action types to query.
For the hunting query development and hunting use-cases, the action types is a great go-to resource.
The columns in the schema reference is clickable and can in a simple way be added to the query
Simple query management
The inspect record pane is an easy way to see the data for one single row. When developing new queries I usually take a subset of data (take/limit 20) to see an overview of the results, and also select an event to see all data instead of side scrolling through all columns when needed.
New features in inspect record is that we can do quick filters which will be added to the query.
In this example we would like to know more about process executions from the C:\AttackTools folder
Last but definitely not least… Link the query results to an incident
This is my favorite, this will reduce the gap and simplify the process between threat hunters, responders, and analysts.
By selecting the relevant events in the result, they can be added to an existing incident, or create a new incidents.
This feature will help organizations to define the threat hunting both in a proactive hunting scenario, and in a reactive, post breach scenario when the hunters will assist analysts and responder with a simplified process.
How to link the data to an incident
To be able to link the data you need to have the following columns in the output
DeviceId/AccountObjectID/AccountSid/RecipientEmailAddress (Depending on query table)
Develop and run the query
Please note, you cannot have multiple queries in the query window when linking to incident
Choose to create a new incident or link to an existing
Run a quick check in your environment to see if you have remote internet-based logon attempts on your devices by looking for RemoteIPType == “Public”. There are other where RemoteIPType is useful, like processes communicating with Internet.
Since it’s a ETL file we can actually open it with any ETL viewer, however, the result is not presented to us in the same way
We can see that Windows Performance Recorder is used under the hood
IMPORTANT, If you plan to use this troubleshooting to find paths for exclusions, be very careful. You might accidently open up your device to threats. If you are not 100% certain of your exclusions, please ask for help!
We have been able to use Live Response for some time now. It’s really great and we can take the response actions we find necessary and download data from the endpoint through the browser session.
Here is a very high level of how the architecture looks for the live response feature
Some things which may be difficult today with the limitations of single session is we can only connect to one machine at the time and automation does not apply for a browser session
If a machine is compromised in any way it’s useful, but if we want to automate the responses or run the same custom playbook for multiple devices we need to use the API
The API can be used both to collect necessary artefacts from devices, and also take remediation actions.
On some events, we’ve presented how to use the Live Response to dump memory and export the dmp files to Azure storage as an example how powerful it is.
Requirements and limitations
Rate limitations for this API are 10 calls per minute (additional requests are responded with HTTP 429).
25 concurrently running sessions (requests exceeding the throttling limit will receive a “429 – Too many requests” response).
If the machine is not available, the session will be queued for up to 3 days.
RunScript command timeouts after 10 minutes.
Live response commands cannot be queued up and can only be executed one at a time.
If the machine that you are trying to run this API call is in an RBAC device group that does not have an automated remediation level assigned to it, you’ll need to at least enable the minimum Remediation Level for a given Device Group.
Multiple live response commands can be run on a single API call. However, when a live response command fails all the subsequent actions will not be executed.
Before you can initiate a session on a device, make sure you fulfill the following requirements:
Verify that you’re running a supported version of Windows.Devices must be running one of the following versions of Windows
A new connector for Microsoft 365 Defender is in public preview in Azure Sentinel. This connector makes it possible to ingest the hunting data into Sentinel
Currently, the Defender for Endpoint Data is available
Go to you Azure Sentinel Instance and select Connectors
Search for Microsoft 365 Defender
Click Open Connector Page
Select which Events you want to ingest
Click Apply Changes
| where ActionType == "RegistryValueSet"
| where RegistryValueName == "DefaultPassword"
| where RegistryKey has @"SOFTWAREMicrosoftWindows NTCurrentVersionWinlogon"
| project Timestamp, DeviceName, RegistryKey
| top 100 by Timestamp
//Process and Network events
union DeviceProcessEvents, DeviceNetworkEvents
| where Timestamp > ago(7d)
| where FileName in~ ("powershell.exe", "powershell_ise.exe")
| where ProcessCommandLine has_any("WebClient",
| project Timestamp, DeviceName, InitiatingProcessFileName,
FileName, ProcessCommandLine, RemoteIP, RemoteUrl, RemotePort, RemoteIPType
If we look at the tables we can see the new created tables
One thing we usually discuss with customers is the workload. Everyone has too much to do and it can, sometimes be difficult to prioritize investigations.
now, where you might be short on staff, and the Covid-19 virus can strike at
the SOC organization or reduce the numbers of available people.
this does not only apply during the world crisis of Covid-19. Automation is
also a help in the normal day to day work.
There are benefits
of being able to automate responses and we have these discussions with many
Automatic self-healing is built-in into Defender ATP and is mimicking these
ideal steps a human would take to investigate and remediate organizational
assets, impacted by a cyber threat.
done using 20 built-in investigation playbooks and 10 remediation actions
at the speed of automation
and remediate all alerts automatically
up critical resources to work on strategic initiatives
will drive down the cost per investigation and remediation
away manual, repetitive tasks
remediation eliminates downtime
value of your protection suite and people, quick configuration and you are up
SecOps Investigation (Manual)
it will take some time from the alert being triggered until someone has the
time to start looking at it. Manual work
also requires more resources for review and approval for each action
SecOPs perspective, an initial response involves information gathering.
Where did the file originate from?
our results, we will decide the remediation steps (if we do not follow a
playbook here, the catch will be different result depending on who makes the
remediation will include connecting remotely or manually collect the device and
then launch tools for the remediation process.
Automatic response with Auto IR
to respond which will avoid additional damage and compromise of additional devices,
when attackers will start moving lateral in the environment.
24/7 buddy who assists the SOC staff to remediate threats so the human staff can
focus on other things
MDATP is sending telemetry data to
MDATP cloud continuously analyzes
the data to detect threats
Once a threat is identitfied an
alert is being raised
The alert kicks off a new automated
AIRS component asks Sense client to
SenseIR is then orchestrated by AIRS
on what action should be executed (Collection/Remediation)
Based on the data collected from the
machine (current and historical) AIRS decides what actions should be taken
For every threat identified, AIRS
will automatically analyze the best course of action and tailor a dedicated
surgical remediation action to be executed using on device components (e.g.
Windows Defender Antivirus)
Playbook is executed
“suspicious host” playbook is just an example of “catch all” playbook that is applied after detailed AutoIR investigation for evidences raised by alerts / incident to ensure that nothing is missed.
processes list – main image, loaded modules, handles, suspicious memory
created files – x minutes febore / after alert
Security Graph eco system – DaaS, AVaaS, TI, TA, Detection engine, ML
TI indicators – for allow / block list
leveraging OS components (e.g. Defender Antivirus) to perform the remediation
(prebuilt into the system, low level actions (driver), tried and tested)
methods (Reg, Link files, etc.) actions
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