130 lines
4.8 KiB
Markdown
130 lines
4.8 KiB
Markdown
# Importing Results Into Elastic Stack
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## Start an elastic stack distribution
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Hayabusa results can easily be imported into Elastic Stack. We recommend using [SOF-ELK](https://github.com/philhagen/sof-elk/blob/main/VM_README.md), a free elastic stack Linux distro focused on DFIR investigations.
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First download and unzip the SOF-ELK 7-zipped VMware image from [http://for572.com/sof-elk-vm](http://for572.com/sof-elk-vm).
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* Username: `elk_user`
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* Password: `forensics`
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When you boot up the VM, you will get a screen similar to below:
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Open Kibana in a web browser according to the URL displayed. For example: http://172.16.62.130:5601/
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>> Note: it may take a while for Kibana to load.
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You should see a webpage as follows:
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## Import the CSV results
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Click the sidebar icon in top-lefthand corner and open `Integrations`.
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Type in `csv` in the search bar and click `Upload a file`:
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After uploading the CSV file, click `Override settings` to specify the correct timestamp format:
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As shown below, perform the following changes and then click `Apply`:
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1. Change `Timestamp format` to `custom`.
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2. Specify the format as `yyyy-MM-dd HH:mm:ss.SSS XXX`
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3. Change the `Time field` to `Timestamp`.
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Now click `Import` in the bottom left-hand corner.
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As shown below, click on `Advanced` and perform the following settings before clicking `Import`:
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1. Title the `Index name` as `evtxlogs-hayabusa`.
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2. Under `Index settings`, add `, "number_of_replicas": 0` so that the index health status does not turn yellow.
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3. Under `Mappings`, change the `RuleTitle` type of `text` to `keyword` so that we can calculate metrics on the rule titles and change the `EventID` type of `long` to `keyword` in order to import without errors.
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4. Under `Ingest pipeline`, add `, "field": "Timestamp"` under the `remove` section. Timestamps will be displayed as `@timestamp` so this duplicate field is not needed. Also, delete the following in order to import without errors:
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```
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{
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"convert": {
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"field": "EventID",
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"type": "long",
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"ignore_missing": true
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}
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},
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```
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Settings should look similar to below:
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After importing, you should receive something similar to below:
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You can now click `View index in Discover` to view the results.
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## Analyzing results
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The default Discover view should look similar to this:
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You can get an overview of when the events happened and frequency of events by looking at the histogram at top.
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In the left-side sidebar, you can add fields you want to display in the columns by clicking the plus sign after hovering over a field:
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To start off, we recommend the following columns:
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Your Discover view should now look like this:
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You can filter with KQL to search for certain events and alerts. For example:
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* `Level: "critical"`: Just show critical alerts.
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* `Level: "critical" or Level: "high"`: Show high and critical alerts.
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* `NOT Level:info`: Do not show informational events, only alerts.
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* `*LatMov*`: Show events and alerts related to lateral movement.
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* `"Password Spray"`: Only show specific attacks such as "Password Spray".
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* `"LID: 0x8724ead"`: Display all activity associated with Logon ID 0x8724ead.
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## Hayabusa Dashboard
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We have exported a simple Hayabusa Dashboard in JSON to download [here](https://github.com/Yamato-Security/hayabusa/blob/main/doc/ElasticStackImport/HayabusaDashboard.ndjson)
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To import the dashboard, open the left sidebar and click `Stack Management` under `Management`.
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After clicking `Saved Objects`, please click `Import` in the upper right-hand corner and import the Hayabusa Dashboard JSON file you downloaded.
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You should now be able to use the dashboard shown below:
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## Future Plans
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We plan on creating Hayabusa logstash parsers and a dashboard pre-built for SOF-ELK so that all you will need to do is copy the CSV results file to a directory in order to ingest the logs.
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## Acknowledgements
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Much of this documentation was taken from the blog write-up in Japanese from @kzzzzo2 [here](https://qiita.com/kzzzzo2/items/ead8ccc77b7609143749).
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Many thanks to @kzzzzo2! |