79 lines
2.5 KiB
Markdown
79 lines
2.5 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 `Import a file`.
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After uploading the CSV file, click `Override settings` to specify the correct timestamp format.
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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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Click on `Advanced` and perform the following settings:
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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 do statistics on the rule titles.
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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.
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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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Level: "critical"
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*LatMov*
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"Password Spray"
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https://qiita.com/kzzzzo2/items/ead8ccc77b7609143749 |