Heap & File Carving

Along with the newly released 2.9 version of Profiler Advanced, we have improved support for memory images.

Before going into the main topics of this post, it is worth mentioning that loading and scanning times have been drastically improved for memory images. Apart from the important internal optimizations, the user is now given the choice of scanning or not the files in memory.

If the user chooses not to scan the files in memory right away (they are still scanned once individually opened in the UI), the loading process of the memory image takes only a few seconds if that.

One of the main news in 2.9 is the support for heap parsing for all Windows versions from Windows XP to Windows 10. The only limitation is that we don’t yet support the new heap type found in Metro/Modern applications. This new type of heap can also be found in certain Windows 10 processes such as: smss.exe, csrss.exe, services.exe, lsass.exe, svchost.exe, MicrosoftEdgeC, etc.

The heap of every process can be inspected in the UI.

It’s not trivial to parse a heap which might also be corrupted because of paged out memory regions. We put effort into parsing what is available.

You might wonder why the effort of parsing the heap in the first place. The main reason was due to a new feature introduced in Profiler 2.9, namely file identification in memory regions. Since we anyway wanted to identify files loaded in memory regions, we thought it was a good idea to try to identify files in the heap as well. Hence, the user can now enable file identification in memory regions and heap.

Of course, the user can inspect all the identified files in the UI. This for instance is an image found in the heap of the dwm process.

The user may also choose to dump all identified files to a specific folder.

The dump output is divided into directories, one for each process.

Each process contains one or all of the following directories and an info.txt file.

The info.txt file contains a list of dumped files and their respective names in the Profiler UI, along with possible errors:

We’ll further improve this feature in the next time, so stay tuned!

Windows Memory Forensics

Let’s begin with an image:

Yep. That’s an icon. In an executable. In a process address space. In a raw memory dump.

And here is the video demonstration:

This is just a proof-of-concept. We still haven’t decided whether to develop this further. It really depends on whether the forensic community is interested in having such a product. So, even a re-tweet will have an impact on our decision. 🙂 We wanted to show what is currently possible and, of course, it’s not the end of the cool things which are possible.

In case we decide to go ahead with the development, we will probably create a beta-test group of potential customers and decide with them a roadmap for a 1.0 version, taking into consideration all those features which are essential to them. What we already support are the Windows versions that go from XP to 10 on the following architectures: x86, x86-PAE, x64. And, of course, the software itself, just like Profiler, runs on Windows, OS X and Linux.

And now to the more technical side if you’re interested. What we have shown in this demonstration is just a Python extension for Profiler. To be more specific, it’s only about 1000 lines of Python code and this includes all the UI views. The bulk of the work went into exposing all the necessary capabilities of our SDK to Python. Of course, all this work also benefits other extensions, not just the memory forensics ones. So, if this project ends with this post, it’s really not a tragedy, as we haven’t lost any significant time developing specific stuff for it.

So why did we choose to write our memory forensics support in Python, rather than in C++, which would’ve taken us a lot less time? The reasons are several. The memory forensic field is always changing rapidly and setting code in stone by compiling it wouldn’t be a good idea. Also, we wanted to give our customers the possibility to inspect the code and to modify it. Just by looking at existing code it’s extremely easy to write new utilities. While on the other hand, having our core engine and UI written in C++, makes our tool very fast. We think this is the perfect combination.

If you’re wondering why we didn’t use Volatility as a backbone, the answer is that it would’ve been incompatible on a licensing level and way too difficult to fit nicely into our existing framework to accomplish what we wanted to do.

We hope you enjoyed the demo and we would be happy to receive your feedback!