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Friday, March 3, 2017

Building a Sysmon Dashboard with an ELK Stack






















Threat Hunting is FINALLY a hot topic, and in the past couple of months the security community has been sharing amazing resources on how to hunt with the help of open source tools. One in particular that has got a lot of attention for endpoint visibility has been Sysmon, and with its latest capabilities added in version 6, hunting even for named pipe pivoting has become easier.

A few projects that I have read recently are awesome, and I highly recommend to take a look at them:



Some of the things that I love about most the projects out there are the different ways how sysmon configs are being put together and how data is being consolidated and presented for hunting campaigns. Therefore, in this post, I will show you how you can also create your own Sysmon dashboard but with the help of an ELK stack. This will help you to tune your initial Sysmon configurations and get a good overview of what you can see and hunt for in your lab. If you haven't yet read my previous series "Setting up a Pentesting... I mean, a Threat Hunting Lab", I recommend you to do it before continuing reading (At least, for the purpose of this post, read and follow the steps in Part 5 & Part 6 in order to be ready to build your dashboard). 




Current Kibana view


If you already have an ELK Stack running and Sysmon logs being forwarded to it, then picture 1 below will look very familiar to you. Even though this view allows you to start running a few queries to create chains of events and detect suspicious activity in your network, it does not give you a high overview of what is actually happening in your environment. I like to know my top events to filter out noise and detect the abnormal. Therefore, I will show you how you can create visualizations of specific events and add them to a dashboard.



Figure 1. Kibana default discover view.





Building a Sysmon Dashboard


Creating Visualizations


To get started click on the option "visualize" on the left panel. Next, you will have two options to choose from:

  • Create New Visualization - Showing different types that you can use to present your data
  • Open a Saved Visualization

Since this is our first visualization, then we will have to select the specific type we want to create. Make sure you review the Kibana User Guide - Creating a Visualization during this section to have a better understanding of each visualization type. 



Figure 2. Visualize options.




I like to use Data Tables because they are really flexible to show long strings of data and large number of events in a small graph. Data Tables  display the raw data of a composed aggregation. Click on Data Table to create one. 



Figure 3. Creating a Data Table.




We are creating all of our visualizations from scratch so select the index that you want to use for it. In my case, I selected my only index, winlogbeat-*.



Figure 4. Creating a Data Table. 




Next, you will get a plain visualization template which you will use to create your own one. One main thing that we need to do is select the data field that we want to use for this table, but first we will have to select a bucket type. The rows of the data table are called buckets. You can define buckets to split the table into rows or to split the table into additional tables [Source]. Select the Split Rows bucket type.  



Figure 5. Creating a Data Table.




Buckets support aggregations. Select the aggregations type "Terms". A terms aggregation enables you to specify the top or bottom n elements of a given field to display, ordered by count of a custom metric [Source]



Figure 6. Creating a Data Table. 




Next, select the field that you want to use for the visualization. For this first exercise, I chose the CommandLine field as shown in figure 8. One important thing to mention is that I use Keyword data fields (Keyword Analyzers) because it returns the entire string as a single token [Source]. For example, I chose event_data.CommandLine.keyword.



Figure 7. Creating a Data Table.





Figure 8. Creating a Data Table.




Then set the number of values that you want to show. The data by default will be ordered "Descending". You can set the size to 25 and it will show you the Top 25 values. Lets set it to 10 for this exercise.



Figure 9. Creating a Data Table. 




Figure 10. Creating a Data Table.




Next, you can also adjust the number of values you want to show per page. This will depend on how much space you want to use with your data table. I always set it to 4 to fit several data tables in one dashboard. 



Figure 11. Creating a Data Table.






Figure 12. Creating Data Table.




Apply the changes to your visualization by clicking on the blue triangle to the right of "options" as shown in figure 13 below. 



Figure 13. Creating a Data Table.




Now you will see events showing on the right side of your visualization console. Four values per page and two pages in the last 15 minutes. 



Figure 14. Creating a Data Table.




Save your visualization by clicking on the option Save. Give it a name and click Save. You will get a dark green confirmation message as shown in figure 18 below.



Figure 15. Saving Data Table.





Figure 16. Saving Data Table.





Figure 17. Saving Data Table.





Figure 18. Saving Data Table.





Creating a new Dashboard


Click Dashboard in the side navigation. If you haven’t previously viewed a dashboard, Kibana displays an empty dashboard [Source]. Click Add  in the menu bar to add your saved visualization to it.



Figure 19. Creating a Dashboard




As you can see, our Top 10 Command Line is the only one available. Click on it and it will get added to your Dashboard.



Figure 20. Creating a Dashboard.




Figure 21. Adding visualization to dashboard.




Next, you can start saving your dashboard with your first visualization by clicking on "Save". Give your dashboard a name and if you want to save it to open always with a specific time range, set the desired time range and click on the "Store time with dashboard" checkbox as shown in figure 26 below.



Figure 22. Saving new dashboard.





Figure 23. Saving new dashboard.





Figure 24. Saving a new dashboard.





Figure 25. Adjusting Time Range for new Dashboard.





Figure 26. Saving dashboard with option "Store time with dashboard".





Figure 27. Saving new dashboard. 





Creating a new visualization for our new dashboard


Let's create a different visualization. Lets select a Pie Chart.


Figure 28. Creating a Pie Chart.





  • Select the data field that you want to use in the visualization
  • Set the number of values to show in the data table
  • Apply Changes



Figure 29. Creating a Pie Chart.




As you can see, in figure 29 above, there is an event id (4656) that does not belong to the Sysmon ones. This is because I am also sending Windows event logs to my ELK stack. An easy fix is just to use the search bar and run a query to show only source_name:"Microsoft-Windows-Sysmon". That will make your visualization to work only with the results of your query which will be only Sysmon logs. 



Figure 30. Creating a Pie Chart.




Next, you can use the options button to change the shape of your graph. I always like to set it to the Donut style. Then, you can save your visualization and add it to your new dashboard the same way how we did it before with our Data table.



Figure 31. Creating a Pie Chart.





How can I exclude specific values in my visualization?


In figure 32 below, my top destination IP value is 172.18.39.103 and the problem with it is that the IP belongs to my own ELK server. Therefore, I need to filter that value out in my visualization. You have 2 options:

  • Add exclusions in your Sysmon Config (Recommended - Best Practice)
  • Create/Apply a filter to you visualization (good exercise for you)



Figure 32. Excluding values in visualization.




For the purpose of this exercise:

  • Click on the value you want to filter out, and it will actually set a filter to only show that value by default
  • Hover over the filter that you just created below the search bar
  • Select the (-) magnifier glass and you will see that the filter turns red which means that the value is now being filtered out



Figure 33. Excluding values in visualization.





Figure 34. Excluding values in visualization.





Figure 35. Excluding values in visualization.





Creating all the needed visualization for our Sysmon Dashboard


Total Sysmon Events - Metric Visualization


By selecting winlogbeat-* index, the Metric Visualization will count all the events in our index. Make sure that if you want only Sysmon logs, you run a query for source_name:"Microsoft-Windows-Sysmon" as shown in figure 36 below.



Figure 36. Sysmon Metrics.





Sysmon Event IDs - Pie Chart Visualization



Figure 37. Sysmon Event IDs.





Registry Event Types - Pie Chart Visualization




Figure 38. Registry Event Types..





Top 10 Granted Access Codes - Pie Chart Visualization 




Figure 39. Granted Access Codes.





Top 10 Destinations -  
Pie Chart Visualization 




Figure 40. Destination IPs.





Top 10 Destination Ports -  Pie Chart Visualization 




Figure 41. Destination Ports.





Top 10 Parent Processes - Data Table Visualization




Figure 42. Parent Processes.





Top 10 Processes - Data Table Visualization




Figure 43. Processes.





Top 10 Command Line - Data Table Visualization




Figure 44. Command Line.





Top 10 Pipe names - Data Table Visualization




Figure 45. Pipe Names.





Top 10 Source Images - Data Table Visualization




Figure 46. Source Images.





Top 25 Images loaded - Data Table Visualization




Figure 47. Images Loaded.





Top 10 Registry Objects - Data Table Visualization




Figure 48. Registry Objects.





Top 10 Files Created - Data Table Visualization




Figure 49. Files Created.





How do I delete visualizations?


  • In the dashboard console click Add and select the option "Manage Visualizations"
  • Click on the checkbox of the visualization as shown in figure 51
  • Select the option "Delete"
  • Confirm that you are deleting the visualization 




Figure 50. Add visualizations console.





Figure 51. Selecting the visualization.





Figure 52. Deleting visualization - Confirmation.





Figure 53. Visualizations.




All the visualizations needed for our Sysmon Dashboard




Figure 54. Visualizations ready.





Saved visualizations added to our Sysmon Dashboard




Figure 55. Sysmon Dashboard.





How do I clean my dashboard or Index?


Stop your Winlogbeat services on your endpoints to stop them from sending logs to your ELK server.



Figure 56. Stopping Winlogbeat service.




On your ELK server delete your index by using the following command:

curl -XDELETE 'localhost:9200/winlogbeat-*?pretty'

https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-delete-index.html 



Figure 57. Deleting Index. .




Refresh your discover view and you dashboard. You will see that there are no records available.



Figure 58. Clean Index.




Figure 59. Clean Dashboard.




Start sending logs back to your ELK Stack


Start your winlogbeat service on your endpoints and refresh your Discover view and Dashboard.



Figure 60. Starting Winlogbeat service.





Figure 61. Discover view.






Final Sysmon Dashboard




Figure 57. Final Sysmon Dashboard.




That's it! In my next posts I will be using the same approach to start creating targeted dashboard hunts for different TTPs. 



Feedback is greatly appreciated!  Thank you.


2 comments:

  1. Your ELK series is fantastic and exactly what I was looking for!!

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    Replies
    1. Hey Marcus! Thank you for the feedback man. I am glad to hear that it is helpful. I will be adding some basic data science concepts/techniques to play with the data from Elasticsearch soon :)

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