The steps in this section assume you are troubleshooting a client that has already enrolled and is actively communicating with the server. If the client is not communicating with the server or has never connected then please see the section Debugging client communications in the Deployment Troubleshooting section.
In the
Deployment troubleshooting section
we explain how to bring up the debug server by providing the --debug
flag on
the command line. However clients are often remote and it’s therefore not always
possible to debug the client by starting it with this flag. Often we are also
trying to troubleshoot an issue that happens while collecting an artifact from a
remote client and we want to see what is actually happening in the client
process itself.
We can debug the client while it is running without starting the debug server
using the artifact Generic.Client.Profile
. This artifact has access to the
same data exposed through the debug server, but does not require the debug flag
to be enabled in advance.
By default the artifact collects the most useful information developers require, but you can customize the artifact parameter to collect more detailed information if required.
You can share the result of the collection by exporting it to a zip file and sharing with the development team on Discord or GitHub issues.
While collecting the profile at any time is useful, it is sometimes
hard to catch the problem on the client at just the right moment. For
example, if a particular query causes a memory leak or performance
issues, by the time you can schedule the Generic.Client.Profile
artifact, the client may have already restarted or is too busy to
actually collect the artifact.
In this case it is useful to enable a trace during the collection of another artifact. This setting will cause the client to take profile snapshots at specified intervals during query execution and automatically upload them to the server.
This setting will upload a zip file containing critical profile information every 10 seconds during query execution. This information is useful to see the memory and resource footprint as the query progresses as well as the logs from the client.
One of the first troubleshooting steps for client-related issues is to run the
client manually from the command line with the -v
flag which prints client
logs to the screen. This helps to identify startup issues or transient network
issues. This is often impractical or impossible when the client is remote and we
have means of access to it other than Velociraptor itself.
We could use the Velociraptor client to collect it’s own plaintext logs from disk, however the client, by default, does not write its logs to disk. This is done to prevent information leakage risks - the client’s log may contain sensitive information such as collected artifacts.
To overcome this, it is possible to tell the client to log to an encrypted local storage file. This allows us to collect the file from the client later and decrypt it on the server while not creating any information leakage risk.
To enable local client logging, you create a new label group
(e.g. logged
) and then assign the Generic.Client.LocalLogs
client
monitoring artifact to this group. This allows you to begin logging on
any client by labeling it so that it joins the group.
Logs will be written continuously into the specified file on the endpoint. The file is encrypted and can only be decrypted on the server but the client can append logging information, even after a reboot.
When we want to inspect the log file, we simply collect it from the
endpoint using the Generic.Client.LocalLogsRetrieve
artifact.
The notebook tab will automatically decrypt the logs and display them in a table.