Malware – Page 7 – Baker Street Forensics

Book Review: Cloud Forensics Demystified

Forensic Imaging, Forensics, M365, Malware, Memory Analysis, RAM, Triage

At this point, we’ve all heard the expression ‘There is no cloud; It’s just someone else’s computer.’ While there is some truth to that, there are some fundamental differences when it comes to digital forensics when cloud resources are part of the investigation.

Recently, I had the chance to read Cloud Forensics Demystified: Decoding cloud investigation complexities for digital forensic professionals, by Ganesh Ramakrishnan and Mansoor Haqanee. I received a complimentary this book in exchange for an honest and unbiased review. All opinions expressed are my own.

I’ve been doing DFIR for about 15 years now. In the early days, almost all investigations involved having hands on access to the data or devices being investigated. As I moved into Enterprise Incident Response, it became more and more frequent that the devices I would be investigating would be in a remote location, be it another state – or even another country. As the scope of my investigations grew, so did my techniques need to evolve and adapt.

Cloud Forensics is the next phase of that evolution. While the systems under investigation may still be in another state or country, extra factors come into play like multi-tenancy and shared responsibility models. Cloud Forensics Demystified does a solid job of shedding light on those nuances.

The book is divided into three parts.

Part 1: Cloud Fundamentals
Part 2: Forensic Readiness: Tools, Techniques, and Preparation for Cloud Forensics
Part 3: Cloud Forensic Analysis: Responding to an Incident in the Cloud

Part 1: Cloud Fundamentals

This section provides a baseline knowledge of the three major cloud providers, Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure. It breaks down the different architectural components of each, and how the platforms each handle the functions of virtual systems, networking and storage.

Part 1 also includes a broad yet thorough introduction to the different Cyber and Privacy legislation that come into play for cloud investigations. This section is not only valuable to investigators. Whether you’re a lawyer providing legal counsel for an organization, or responsible for an organizations overall security at a CISO level, this material is beneficial in understanding the challenges and responsibilities that come from hosting your data or systems in the cloud, and the different legislation and regulations that follow those choices.

Part 2: Forensic Readiness: Tools, Techniques, and Preparation for Cloud Forensics

As with enterprise investigations, logging is often where the hunting for incident indicators begins with telemetry and the correlation of different log sources. This section focuses on the different log sources available in AWS, GCP, and Azure. It also provides a detailed list of log types that are enabled by default and those that require manual activation to ensure that you have access to the most relevant data for your investigations when an incident occurs. This section also covers the different providers offerings for log analysis in the cloud including AWS Cloud Watch, Microsoft Sentinel and Google’s Cloud Security Command Center (Cloud SCC) as examples.

Part 3: Cloud Forensic Analysis: Responding to an Incident in the Cloud

As an Incident Responder, this was the section I enjoyed the most. While the first two sections are foundational for understanding the architectures of networking and storage, part three provides detailed information on how to acquire evidence for cloud investigations. The section covers both log analysis techniques as well as recommendations for host forensics and memory analysis tools. The book covers the use of commercial forensic suites, like Magnet Axiom, as well as open-source tools like CyLR and HAWK. Besides covering investigations of the three Cloud Service Providers (CSPs), there is also a section covering the cloud productivity services of Microsoft M365 and Google Workspace, as well as a brief section on Kubernetes.

Summary

Whether you’re a gray-haired examiner like me, or a neophyte in the world of digital forensics, chances are high that if you’re not running investigations in the cloud yet – you will be soon enough. Preparation is the first step in the Incident Response lifecycle. To properly prepare for incidents you need to know both what sources will be most informative to your investigations, as well as the methodology to capture and process that evidence efficiently.

Cloud Forensics Demystified is a comprehensive guide that covers cloud fundamentals, forensic readiness, and incident response. It provides valuable insights into cloud investigation techniques, log analysis, and evidence acquisition for major cloud providers and productivity services. The book is valuable for both experienced and novice digital forensics professionals to prepare for cloud investigations.

Beyond Hashes: Simplifying Malware Identification with Python and MpCmdRun

DFIR, Forensics, Malware, PowerShell, Python

In an earlier post titled “Growing Your Malware Corpus”, I outlined methods for building a comprehensive test corpus of malware for detection engineering. It covers using sources like VX-Underground for malware samples and details how to organize and unzip these files using Python scripts.

In today’s post we’re going to cover using Python to apply a standard naming methodology to all our malware samples.

Depending on where you curate your samples from, they could be named by their hash, or as they were identified during investigation, like invoice.exe. Depending on the size of your collection, I’d surmise it’s highly unlikely that they have a consistent naming format.

I don’t know about you, but a title that indicates the malware family and platform is a lot more useful to me than a hash value when perusing the corpus for a juicy malware sample. We can rename all our malware files using Python and the command line utility for Windows Defender.

Step 1: You’ll need to install Python on a Windows box that has Windows Defender.

Install Python

If you don’t have Python installed on your Windows machine, you can do so by downloading the installer from python.org, or alternatively, installing from the Windows store.

*Windows Store installer for Python versions 3.7 to 3.12*

Directory Exclusion

Within the Windows Defender Virus & Threat protection settings, add an exclusion for the directory you’re going to be using with the malware. Make sure the exclusion is in place before connecting the drive with the malware so it doesn’t get nuked.

Note: Doing this assumes you’ve evaluated the potential risks associated with handling malware, even in controlled settings, and have taken safety precautions. This is not an exercise to be conducted on your corporate workstation.

*Screenshot of the D:\Malware Directory being excluded from Windows Defender.*

Automatic Sample submission

It’s up to you if you want to disable the Automatic Sample submission. If you do, you’ll still may get prompted to send some.

*Windows Defender requesting to send samples to Microsoft for further analysis.*

Rename_Malware.py

The star of this show is the python script that was shared on ~~twitter~~ from vx-underground.

The post walks through various options for utilizing Windows Defender command line, MpCPmdRun.exe. Using that information a Python script was developed to loop through the contents of a directory, analyze those files with Windows Defender, and then rename the files accordingly based on the malware identification.

*Python code for rename_malware.py in VS Code.*

You can grab the code from the linked post, or a copy on my Github here.

Once you’ve got Python installed, directory exclusion configured, and a pocketful of kryptonite (malware), – you’re ready to go.

python rename_malware.py D:\Malware

Windows Defender command line will run through each file and rename them based on its detection.

*The script recursively renames the analyzed files.*

I’m running this on a copy of my malware corpus of 30,000+ malware samples.

Counting the Corpus

A bit of handy PowerShell math. Before and after the process I wanted to be sure of how many files were present to ensure that the antivirus didn’t remove any. I also wanted to exclude counting pdfs as many of the samples in my corpus also have accompanying write-ups.

*Using PowerShell for selective file counting.*

Get-ChildItem -Recurse -file | Where-Object { $_.Extension ne *.pdf" } | Measure-Object | Select Count

Back at the console the script is still running.

*The script continues recursively renaming the analyzed files.*

Finally… not begrudgingly at all considering over 30,000 samples were analyzed, the script has reached the end of the samples.

*Script has reached the end of the files.*

If we do a directory listing on the contents of the malware directory, we see that the majority of the files have all been renamed based on their malware identification.

*File listing showing malware files named Trojan.Powershell… Trojan.Script… etc.*

Hooray!

That makes it much easier to search and query through the malware repository.

The last step… make a BACKUP. 😉

Growing Your Malware Corpus

DFIR, Malware, Python, yara

If you’re writing YARA rules or doing other kinds of detection engineering, you’ll want to have a test bed that you can run your rules against. This is known as a corpus. For your corpus you’ll want to have both Goodware (known good operating system files), as well as a library of malware files.

One source to get a lot of malware samples is from VX-Underground. What I really appreciate about VX-Underground is that in addition to providing lots of malware samples, they also produce an annual archive of samples and papers. You can download a whole year’s worth of samples and papers, from 2010 to 2023.

Pandora’s Box

Just to understand the structure here, I have a USB device called “Pandora.” On the root of the drive is a folder called “APT”, and within that is a “Samples” directory. Inside the samples directory is the .7z download for 2023 from VX-Underground. There’s also a python script… we’ll get to that soon enough.

The first thing we’ll need to do is unzip the download with the usual password.

7zz x 2023.7z

Once the initial extraction is complete you can delete the original 2023.7z archive.

Within the archive for each year, there is a directory for the sample, with sub-directories of ‘Samples’ and ‘Papers.’ Every one of the samples is also password protected zip file.

This makes sense from a safety perspective, but it makes it impossible to scan against all the files at once.

Python to the Rescue

We can utilize a Python script to recursively go through the contents of our malware folder and unzip all the password protected files, while keeping those files in their original directories.

You may have noticed in the first screenshot that I have a script called ExtractSamples.py in my APT directory.

We will use this for the recursive password protected extractions.

Python ExtractSamples.py

A flurry of code goes by, and you congratulate yourself on you Python prowess. Now if we look again at our contents, we’ve got the extracted sample and the original zip file.

Let’s get rid of all the zip files as we don’t need them cluttering up the corpus.

We can start by running a find command to identify all the 7zip files.

find . -type f -name '*.7z' -print

After you’ve checked the output and verified the command above is only grabbing the 7z files you want to delete, we can update the command to delete the found files.

find . -type f -name '*.7z' -delete

One more a directory listing to verify:

Success. All the 7z files are removed and all the sample files are intact.

GitHub Link: ExtractSamples.py

Time to go write some new detections!

Huntress CTF: Week 2 – Malware: VeeBeeEee, Snake Eater, Opendir

CTF, DFIR, Malware

VeeBeeEee

First examine the file contents.

Ooof. That hurts the eyes. If we throw it into CyberChef, with the assistance of some magic (or detailed reading of the challenge), we see that it’s VB Script, which can be converted using the Microsoft Script Decoder recipe.

Copy the output to VS Code.

The syntax highlighting shows that all the ””””””””al37ysoeopm’al37ysoeopm entries are just comments, so let’s remove them.

There also seems to be an abundance of “&” obscuring the code. We’ll remove them too.

That’s a lot more readable. Looking at the code we see it’s going to use PowerShell to create a file C:\Users\Pubic\Documents\July.htm using as input the content from a pastebin URL.

Snake Eater

We’ll detonate snake_eater.exe in our lab environment.

I really enjoyed this challenge as I used my detonaRE PowerShell script to control the detonation and solve the challenge. Besides firing the malware itself, the script will initiate a pcap capture and monitor the malware process using Process Monitor. The script the converts the ProcMon output to csv for easy analysis.

Scrolling through the csv we find that the application was writing a file to:

~\AppData\Roaming\Mael Horns\flag{hashforflag}

Opendir

Let’s get Started

The link brings us to an Open Directory (duh) with lots of scripts and executables, not to mention a number of subdirectories.

The first thing to do is grab everything.

Site Sucker works well for this.

Once we’ve captured all the files and subdirectories locally we can search through them en masse. Once again in this CTF, the_silver_searcher (ag) comes into play.

Tucked away in /sir/64_bit_new/oui.txt is the flag.

Use the tag #HuntressCTF on BakerStreetForensics.com to see all related posts and solutions for the 2023 Huntress CTF.