The year was 2008, and I had been staying at a hotel in Bogota. This trip was just one of many to Columbia that year. Before my trip, I’d had my former girlfriend, Darci, stop by and help me swap out the hard drive in my MacBook Pro laptop. Remember, this is 2008, and at the time, replacing a drive in a MacBook Pro wasn’t nearly as easy as replacing hard drives these days. Darci swapped out my original hard drive with a brand-new drive, which I then formatted and installed macOS.  I had her swap the drive out for security reasons. I didn’t want to cross the border into a foreign country with all of my client data. Especially not after what happened to me in Atlanta! But we’ll get to that later.

Modern encryption tools employ strong encryption with multiple hash iterations, making passwords extremely difficult to break. The November article “What is password recovery and how it is different from password cracking” explains the differences between instantly accessing protected information and attempting to break the original plain-text password. In that article, I briefly mentioned GPU acceleration and distributed attacks as methods to speed up the recovery. In this article, I’ll discuss the two acceleration techniques in more detail.

Modern applications use highly secure and thus deliberately slow algorithms for verifying passwords. For this reason, the password recovery process may take a lot of time and require extreme computational resources. You can build your own powerful cluster to accelerate brute-force attacks, but if you only need to recover a password every once in a while, maintaining your own cluster may not be the best investment. Cloud services can help do a one-off job faster. For a long time, Elcomsoft Distributed Password Recovery had supported Amazon cloud services with automatic deployment on Amazon’s powerful GPU-accelerated servers. The latest update brings support for Microsoft Azure, adding the ability to automatically deploy Password Recovery Agents to virtual machines created in Microsoft Azure. In this article I will describe the deployment steps.