GrrCon 2015 - Memory Forensics - Grabbing all the Flags...

Today we bring you a special guest posting by Tony "@captcook32" Cook. Late last year GrrCon hosted their anticipatory excellent set of challenges which included an in depth memory forensics challenge by Wyatt Roersma. Tony and myself took a few days on a down week to try our hand at the challenge. I lacked the answers to two questions while Tony knocked them all out quickly.

While the scoreboard was reset to before our scores were posted, I'd like to present Tony's write-up on the challenge. The challenge files are still available for download, so feel free to try the challenge on your own and return for hints. Next to each question is the file required to answer it and the password needed to open the archive.

And so follows Tony Cook:

In October 2015 Google put on the GrrCon 2015 CTF challenge which was open to all who wanted to attempt the challenge. My colleague "The Brian Baskin" @bbaskin let me know it was going on & I wanted to test out my memory forensics skills so I gave it a shot. This was one of the most fun & valuable CTFs that I've ever done. I want to give a huge shout out the the Volatility team for their awesome product & for the GrrCon 2015 CTF team for having a semi real world challenge that made you think outside of the box. The following blog post is my walkthrough of how I got through the challenge. There are most likely far better ways to go about doing most of these & I don't claim to be a memory forensic expert but I hope this helps out anyone who got stuck on any of the questions &/or anyone looking for an explanation. 

Question #1

We start out with a question letting us know that user opened a "strange" email that appeared to be a security update, kudos to the CTF creators because who hasn't seen that happen... All we need to provide is the sender's email address. As with all of these questions there are about a million different approaches that we could take to find the answer, however, the way my lazy mind works I wanted to start by finding all the email addresses within the memory dump, then use that list to grep through the memory dump for these email addresses to hope for an email that would resemble the user's . So to start with I utilized Garfunkel amazing tool, the Bulk Extractor. Among several other options this tool can provide you with a histogram of email addresses which will provide us a starting point to start looking through the memory dump.

Creating a Malware Sandbox in Seconds with Noriben.

Happy New Years!

As part of the new year, let's make an effort to make your defensive posture better, especially through quicker and more effective malware analysis! A few years ago I created a sample malware analysis sandbox script to use for the analysis and reverse engineering that I performed on a daily basis. Let's show how you can perform analysis of malware within just a few seconds with almost no setup at all.

1. Introduction
2. Automating Sandboxing with VMware
3. How you can help! Even with no technical background!
4. Download Information

For those who are already familiar with Noriben, feel skip to the second section to see the new content.

[UPDATE: In the year since this was written, I've made a new Python-based frontend. You'll find it in the same repo as NoribenSandbox.py. It's a much better option for many.]

Introduction

If you've followed me on Twitter, or kept up with this blog, you would be familiar with Noriben. If not, it's a very simple script. In typical behavior analysis one would run malware within a sandbox to see exactly what files it creates, what processes it runs, and what changes it makes to the system. The most common way that many defense teams use is to upload the file to a central anti-virus testing site like VirtusTotal and to online sandboxes like Malwr and those using Cuckoo.

For teams who are leery of uploading their files to the Internet, which is especially inadvisable for APT-related investigations. As advanced actors monitor online sites to see if their files are uploaded, they can determine if their free reign within the environment comes to an end and an IR response has started.

Running malware locally is most commonly performed through Cuckoo, an awesome and open-source sandbox application designed for malware that produces very comprehensive results. However, there is is arguably considerable effort required to set up Cuckoo correctly, with multiple sites offering walkthroughs for various environments. While relatively easy to install on Linux, installing on Windows or OSX can be frustrating for many. And, in my case, I'm often on the road with a random laptop and need to make a sandbox very quickly.

If you take a malware analysis training course, you've also likely been exposed to the SysInternals Procmon tool to monitor a system's environment. For those with more vintage knowledge, you learned Regmon and Filemon. Others use Regshot, a tool that is inadequate for many malware as it doesn't track finite changes within runtime.

Noriben is a simple wrapper for Procmon to collects hundreds of thousands of events then uses a custom set of whitelisted system events to reduce this down to a few dozen for quick review. For more, take a look at the slide deck I put together for the 2015 Black Hat Arsenal:

DJ Forensics: Analysis of Sound Mixer Artifacts

In many forensics examinations, including those of civil and criminal nature, there is an art to finding remnants of previously installed applications. Fearing detection, or assuming that an examination is forthcoming, many suspects attempt to remove unauthorized or suspicious applications from a system. Such attempts are usually unsuccessful and result only in additional hours of processing for forensics. But even with a clean uninstall there are traces left within the Windows registry that note such a program was installed.

The most popular of these is the Windows Shim Cache (a/k/a Application Compatibility Database, a/k/a AppCompatCache), a resource that can be used to catalog applications not natively compiled for newer Windows. It's also a resource that works great for finding APT-related malware running on a system, but not so much legitimate applications.

For a few months I've been playing with another repository of applications: the Windows Sound Mixer. Whenever an application requests the use of the Windows audio drivers, Windows will automatically register this application in the registry. This information is stored so that Windows can create per-application sound settings:

This was a resource I dismissed for a year. It existed only in Windows Vista and newer, it didn't catch any of the malware I threw at it, and wasn't relevant to any of the Incident Response work I do**. Its importance came to me when working some cases that came mixed in with many of my intrusion cases where I had to examine the systems owned by various hackers. One in particular involved tracking the use of alternative web browsers and discovering that the Sound Mixer had catalogued the use, and location, of Tor Browser launched from a TrueCrypt volume. Clear as day, the path even noted that it was a TrueCrypt volume based upon the Windows device name:

\Device\TrueCryptVolumeP\Tor\App\Firefox\firefox.exe

I learned that the registry keys were useful for such cases, but there has been no prior public discussion of the forensic use of this data.

A GhettoForensics Look Back on 2013

This site, Ghetto Forensics, was started this year as the beginning of an effort to better document some of the side work that I do that I thought would be appealing, or humorous, to the overall industry. This content was originally posted to my personal web site, thebaskins.com, but really needed a site of its own.

My first public project this year was reversing, documenting, and writing a parser for Java IDX files, cached files that accompany any file downloaded via Java. It was a bit of a painful project, mainly due to the bad documentation provided by Oracle, not to mention the horrendous style in which they designed it. I immediately released the code to the public and have received great feedback for improvements, as well as quite a few examiners touting how much they used it in their examinations. Thank you!

However, my greatest project this year was the release of Noriben. I first designed Noriben as a simple script for me to use at home for really quick malware dynamic analysis. I lacked many of the tools and sandboxes that I use at my day job, and needed a quick triage tool for research. After a few months, I realized that many commercial groups were in the exact same situation as I was at home: a severe lack of funding to purchase software to help. So, I cleaned up the code, gave it a silly name, and released it into the world. I've received numerous feedback and suggestions from all over, all of which were incorporated into the code. While its usage is widely unknown, for practical reasons, I did learn of quite a few Defense organizations, as well as a handful of Fortune organizations that incorporated it into their workflow. Awesome!

Research-wise, I released a comparison of various Java disassembly and decompilation tools, having found the standard JD-GUI to be extremely lacking for modern Java malware. The positive side of this is introducing tools to security professionals that were previously unknown to them. The research itself changed the tools that I use on a regular basis and allowed me to create a better product, faster, for reversing Java applications.

For community projects, I wrote a small malware configuration dumper template for Volatility, based on some time-reducing work I've been practicing. Whenever I do a full reversal of malware, I now try to write a memory configuration dumper. That way, in a few months when they change the encryption routine, I can still retrieve the same configuration and getting the report out instantly, then go back and figure out the encryption.

Dumping Malware Configuration Data from Memory with Volatility

When I first start delving in memory forensics, years ago, we relied upon controlled operating system crashes (to create memory crash dumps) or the old FireWire exploit with a special laptop. Later, software-based tools like regular dd, and win32dd, made the job much easier (and more entertaining as we watched the feuds between mdd and win32dd).

In the early days, our analysis was basically performed with a hex editor. By collecting volatile data from an infected system, we'd attempt to map memory locations manually to known processes, an extremely frustrating and error-prone procedure. Even with the advent of graphical tools such as HBGary Responder Pro, which comes with a hefty price tag, I've found most of my time spent viewing raw memory dumps in WinHex.

The industry has slowly changed as tools like Volatility have gained maturity and become more feature-rich. Volatility is a free and open-source memory analysis tool that takes the hard work out of mapping and correlating raw data to actual processes. At first I shunned Volatility for it's sheer amount of command line memorization, where each query required memorizing a specialized command line. Over the years, I've come to appreciate this aspect and the flexibility it provides to an examiner.

It's with Volatility that I focus the content for this blog post, to dump malware configurations from memory.

For those unfamiliar with the concept, it's rare to find static malware. That is, malware that has a plain-text URL in its .rdata section mixed in with other strings, and other data laid bare in plain sight. Modern malware tends to be more dynamic, allowing for configurations to be downloaded upon infection, or be strategically injected into the executable by its author. Crimeware malware (Carberp, Zeus) tend to favor the former, connecting to a hardcoded IP address or domain to download a detailed configuration profile (often in XML) that is used to determine how the malware is to operate. What domains does it beacon to, on which ports, and with what campaign IDs - these are the items we determine from malware configurations.

Other malware rely upon a known block of configuration data within the executable, sometimes found within .rdata or simply in the overlay (the data after the end of the actual executable). Sometimes this data is in plain text, often it's encoded or encrypted. A notable example of this is in Mandiant's APT1 report on TARSIP-MOON, where a block of encrypted data is stored in the overlay. The point of this implementation is that an author can compile their malware, and then add in the appropriate configuration data after the fact.

As a method to improving the timeliness of malware analysis, I've been advocating for greater research and implementation of configuration dumpers. By identifying where data is stored within the file, and by knowing its encryption routine, one could simply write a script to extract the data, decrypt it, and print it out. Without even running the malware we know its intended C2 communications and have immediate signatures that we can then implement into our network defenses.

While this data may appear as a simple structure in plaintext in a sample, often it's encoded or encrypted via a myriad of techniques. Often this may be a form of encryption that we, or our team, deemed as too difficult to decrypt in a reasonable time. This is pretty common, advanced encryption or compression can often take weeks to completely unravel and is often left for when there's downtime in operations.

What do we do, then? Easy, go for the memory.

We know that the malware has a decryption routine that intakes this data and produces decrypted output. By simply running the malware and analyzing its memory footprint, we will often find the decrypted results in plaintext, as it has already been decrypted and in use by the malware.

Why break the encryption when we can let the malware just decrypt it for us?