In yesterday’s diary, we took a look at two methods that allow to capture network connection information off a potentially compromised virtual machine in Azure. Today, we’ll investigate the most recent addition to the VM monitoring arsenal, namely “Azure Monitor Insights”.
“Insights” is enabled directly under the “Monitoring” menu tab of the corresponding VM. Deploying it can be done from within the Azure Portal, while a VM is running, and without having to log in on the VM itself. The solution deploys a Microsoft OMS monitoring agent into the VM though, so this isn’t exactly stealthy either.
Unlike the two methods shown in yesterday’s diary, “Insights” combines process telemetry from within the VM with network flow logs. The resulting charts are meant well, but get unwieldy very quickly. Behind the charts, there is though a lot of data that can be reached via click-through:
In this case, we can see that the process “wget” made connections on Port 80 and 443, and in the details pane, we can even see the start time, working directory, and the command line used.
But wait, there’s more. The “Insights” chart panel is just visualizing information that is also directly accessible, in the associated Azure Log Analytics container. With the right query in Kusto Query Language (KQL), we can search, combine, merge and dice directly on the logs themselves. This allows for example to quickly identify which process (if any) is leaking or uploading large volumes of data, and to where:
When you experiment with Insights for the first time, keep an eye on the related costs. The pricing model of Azure Monitor Insights is a bit unpredictable, and depends on the volume stored in the associated Log Analytics container. If you have a busy machine that generates a lot of log data, the “free” 5GB allotment in the current Pay-as-you-go pricing model can be used up quite quickly. See https://azure.microsoft.com/en-us/pricing/details/monitor/ for details.
If you have additional tips on how to conduct forensic network monitoring on Azure VMs, please let us know, or share in the comments below.
(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.
Source: Read More (SANS Internet Storm Center, InfoCON: green)