In DFIR Triaging means to quickly collect information about the system in order to establish its potential relevance to a forensic investigation.
While many think of triage as a collecting files (perhaps as an alternative to full disk acquisition), in Velociraptor, there is no real difference between collecting files or other non-volatile artifacts: Everything that Velociraptor collects is just a VQL Artifact.
We like to think of triage as simply capturing machine state - where
the state may be bulk files (like the
$MFT or registry hives) or any
other volatile data, such as process information, network connections
Being able to efficiently and quickly collect and preserve evidence is important for being able to capture machine state at a point in time. It is also useful to be able to use these collected files with other forensic tools that might be able to handle the file formats involved.
One of the most commonly used artifact is the
Windows.KapeFiles.Targets artifact. This artifact is automatically
built from the open source
While originally developed to support the non-opensource Kape tool, this repository contains many types of files which might be relevant to collect in a triage scenario. Each Kape “Target” is essentially a glob expression with a name.
Windows.KapeFiles.Targets is the most popular
artifact for mass file collection. It does no analysis but simply
collects a bunch of files based on the targets specified.
Start by selecting the artifact from the “New Collection” wizard
Next we need to select the “Targets” in the “Configure Parameters”
step. Many targets are simply collections of other targets. For
_BasicCollection target automatically includes a number
of other useful targets.
Windows.KapeFiles.Targets artifact can transfer a large quantity
of data from the endpoints, and take a long time to run. We therefore
often need to update the resource control of the collection.
Once the collection is launched, we can monitor progress in the “Artifact Collection” tab.
Velociraptor is very careful about the performance and resource impact on endpoints. When collecting many files if it is often hard to determine in advance how much data will be collected or how long it will take. For safety, Velociraptor allows limits to be set after which the collection is cancelled. You can also interactively cancel the collection by clicking the “Stop” button.
Be aware that a lot of data can be collected which might fill up the VM disk.
Math is a harsh mistress: Collecting 100Mb from 10,000 endpoints = 1Tb
Note that typically $MFT is around 300-400Mb so collecting the $MFT from many endpoints is going to be huge!
We have seem previously how to collect many files using the
Windows.KapeFiles.Targets artifact in the usual client/server
mode. But what if we are unable to deploy Velociraptor on a new
network in client/server mode? With Velociraptor not installed on the
endpoint, how shall we collect and triage artifacts?
Velociraptor is just a VQL engine! All we need is Velociraptor to be able to collect the VQL artifacts into a file, and then we can transport the file ourselves for analysis. Velociraptor does not really need a server…
Often we rely of an external helper (such as a local admin) to actually perform the collection for us. However, these helpers are often not DFIR experts. We would like to provide them with a solution that performs the required collection with minimal intervention - even to the point where they do not need to type any command line arguments.
Offline collector aims to solve this problem. Velociraptor
allows the user to build a specially configured binary (which is
actually just a preconfigured Velociraptor binary itself) that will
automatically collect the artifacts we need.
Velociraptor allow us to build such a collector with the GUI using an intuitive process.
Select the offline collector builder from the
page. The artifacts selection page and the parameters page are exactly
the same as previously shown.
Next select the collector configuration page.
Here we get to choose what kind of collector we would like:
Target Operating System: This specifies the specific version of the Velociraptor binary that will be packed.
Password: It is possible to specify a password to encrypt the zip
file that Velociraptor will create. Note that when specifying a zip
password, Velociraptor will create a second zip file called
data.zip inside the output zip file. This is done because Zip
password protection does not extend to the directory listing, so
Velociraptor will hide the content of the zip by storing the data in
an embedded zip.
Collection Type: This controls where the collection is stored.
Zip Archive: The collection will be stored in a zip file in the same directory the collector is launched from.
Google Cloud Bucket: The zip file will be uploaded to a cloud bucket. When selecting this you can provide GCP credentials to control the upload bucket.
AWS Bucket: The zip file will be uploaded to a cloud bucket. When selecting this you can provide AWS credentials and details to control the upload bucket.
SFTP: This allows the collector to upload the file to an SFTP server using a private key.
Offline Collector Builder is simply a GUI wrapped around the
Server.Utils.CreateCollector server artifact. Once it is collected,
the artifact will automatically upload the pre-configured collector it
created into the collection and the file will be available for
download from the “Uploads” tab. Simply click on the link to get the
Once the collector is run without command line arguments, the collection will automatically start. No need for the user to enter command line parameters, although they do need to be running in an elevated administrator shell.
The collector creates a zip file containing the collected files as well as an optional report.
Sometimes we want to collect the output from other third party executables. It would be nice to be able to package them together with Velociraptor and include their output in the collection file.
Velociraptor fully supports incorporating external tools. When creating the offline collection, Velociraptor will automatically pack any third party binaries it needs to collect the artifacts specified.
By having a single executable collector, all we need is to run it
remotely. We can use another EDR solution that allows remote execution
if available. Alternatively, we can use Window’s own remote management
mechanisms (such as PsExec or WinRM) to deploy our binary across the
network. Simply, copy our collector binary across the network to C$
share on the remote system and use, e.g.
wmic to launch our binary
on the remote host.
We can use the offline collector to fetch multiple artifacts from the endpoint. The results consist of bulk data as well as JSON file containing the result of any artifacts collected.
You can re-import these collection into the GUI so you can use the same notebook port processing techniques on the data. It also allows you to keep the results from several offline collections within the same host record in the Velociraptor GUI.
Offline collection + Import is very similar to client/server except that instead of the client connecting over the internet, the data is delivered via sneakernet!
Importing an offline collection can be done via the
Server.Utils.ImportCollection artifact. This artifact will inspect
the zip file from a path specified on the server and import it as a
new collection (with new collection id) into either a specified client
or a new randomly generated client.
Offline collections are typically very large, this is why we do not have a GUI facility to upload the collection zip file into the server. You will need to use an appropriate transfer mechanism (such as SFTP or SCP) to upload to the server itself.
Local collection can be done well without a server and permanent agent installed. A disadvantage is that we do not get feedback of how the collection is going and how many resources are consumed.
Offline collections are typically planned in advance and it is a bit more difficult to pivot and dig deeper based on analysis results to search for more results. For this reason offline collections tend to err on the side of collecting more data rather than being more targeted and focused on answering the investigative questions.