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Digital Forensics: Volatility – Analyzing a Malicious VPN

Welcome back, my aspiring digital investigators!

Many of you enjoyed our earlier lessons on Volatility, so today we will continue that journey with another practical case. It is always great to see your curiosity growing stronger. This time we will walk through the memory analysis of a Windows machine that was infected with a stealer, which posed as a VPN app. The system communicated quietly with a Command and Control server operated by a hacker, and it managed to bypass the network intrusion detection system by sending its traffic through a SOCKS proxy. This trick allowed it to speak to a malicious server without raising alarms. You are about to learn exactly how we uncovered it.

What Is a NIDS ?

Before we jump into memory analysis, let’s briefly talk about NIDS, which stands for Network Intrusion Detection System. A NIDS watches the network traffic that flows through your environment and looks for patterns that match known attacks or suspicious behavior. If a user suddenly connects to a dangerous IP address or sends strange data, the NIDS can raise an alert. However, attackers often try to hide their communication. One common method is to use a SOCKS proxy, which allows the malware to make its malicious connection indirectly. Because the traffic appears to come from a trusted or unknown third party instead of the real attacker’s server, the NIDS may fail to flag it.

Memory Analysis

Now that we understand the background, we can begin our memory investigation.

Evidence

In this case we received a memory dump that was captured with FTK Imager. This is the only piece of evidence available to us, so everything we discover must come from this single snapshot of system memory.

showing evidence for the analysis

Volatility Setup

If you followed the first part of our Volatility guide, you already know how to install Volatility in its own Python 3 environment. Whenever you need it, simply activate it:

bash$ > source ~/venvs/vol3/bin/activate

activating volatility

Malfind

Volatility includes a helpful plugin called malfind. In Volatility 3, malfind examines memory regions inside processes and highlights areas that look suspicious. Attackers often inject malicious code into legitimate processes, and malfind is designed to catch these injected sections. Volatility has already announced that this module will be replaced in 2026 by a new version called windows.malware.malfind, but for now it still works the same way.

To begin looking for suspicious activity, we run:

bash$ > vol -f MemoryDump.mem windows.malware.malfind

volatility malfind scan

The output shows references to a VPN, and several processes stand out as malicious. One in particular catches our attention: oneetx.exe. To understand its role, we need to explore the related processes. We can do that with pslist:

bash$ > vol -f MemoryDump.mem windows.pslist | grep -E "5896|7540|5704"

volatility widows pslist listing processes

We see that oneetx.exe launched rundll32.exe. This is a classic behavior in malware. Rundll32.exe is a legitimate Windows utility that loads and executes DLL files. Hackers love using it because it allows their malicious code to blend in with normal system behavior. If the malware hides inside a DLL, rundll32.exe can be used to run it without attracting much attention.

We have confirmed the malicious process, so now we will extract it from memory.

Analyzing the Malware

To analyze the malware more deeply, we need the actual executable. We use dumpfile and provide the process ID:

bash$ > vol -f MemoryDump.mem windows.dumpfile --pid 5896

dumping the malware from the memory

Volatility will extract all files tied to the process. To quickly locate the executable, we search for files ending in .exe:

bash$ > ls *exe*

Once we find the file, we calculate its hash so that we can look it up on VirusTotal:

bash$ > md5sum file.0x….oneetx.exe.img

hashing the malware
malware analysis on virus total

The malware is small, only 865 KB. This tells us it is a lightweight implant with limited features. A full-featured, multi-purpose implant such as a Sliver payload is usually much larger, sometimes around sixteen megabytes. Our sample steals information and sends it back to the hacker.

Viewing its behavior reveals several MITRE ATT&CK techniques, and from that we understand it is a stealer focused on capturing user input and collecting stolen browser cookies.

mitre malware info

Next, we want to know which user launched this malware. We can use filescan for that:

bash$ > vol -f MemoryDump.mem windows.filescan | grep "oneetx.exe"

volatility filescan

It turns out the user was Tammam, who accidentally downloaded and executed the malware.

Memory Protection

Before we continue, it is worth discussing memory protection. Operating systems apply different permissions to memory regions, such as read, write, or execute. Malware often marks its injected code regions as PAGE_EXECUTE_READWRITE, meaning the memory is readable, writable, and executable at the same time. This combination is suspicious because normal applications usually do not need this level of freedom. In our malfind results, we saw that the malicious code was stored in memory regions with these unsafe permissions.

volatility memory protection

Process Tree

Next, we review the complete process tree to understand what else was happening when the malware ran:

bash$ > vol -f MemoryDump.mem windows.pstree

volatility process tree

Two processes draw our attention: Outline.exe and tun2socks.exe. From their PIDs and PPIDs, we see that Outline.exe is the parent process.

Tun2socks.exe is commonly used to forward traffic from a VPN or proxy through a SOCKS interface. In normal security tools it is used to route traffic securely. However, attackers sometimes take advantage of it because it allows them to hide communication inside what looks like normal proxy traffic.

To understand how Outline.exe started, we trace its PID and PPID back to the original parent. In this case, explorer.exe launched multiple applications, including this one.

volatility psscan

Normally we would extract these executables and check their hashes as well, but since we have already demonstrated this process earlier, we can skip repeating it here.

Network Connections

Malware usually communicates with a Command and Control server so the hacker can control the infected system, steal data, or run remote commands. Some malware families, such as ransomware, do not rely heavily on network communication, but stealers typically do.

We check the network connections from our suspicious processes:

bash$ > vol -f MemoryDump.mem windows.netscan | grep -iE "outline|tun2socks|oneetx"

volatility netscan

Tun2socks connected to 38.121.43.65, while oneetx.exe communicated with 77.91.124.20. After checking their reputations, we see that one of the IPs is malicious and the other is clean. This strongly suggests that the attacker used a proxy chain to hide their real C2 address behind an innocent-looking server.

virus total malicious ip
virus total clean ip

The malicious IP is listed on tracker.viriback.com, which identifies the malware family as Amadey. Amadey is known for stealing data and providing remote access to infected machines. It usually spreads through phishing and fake downloads, and it often hides behind ordinary-looking websites to avoid suspicion.

c2 tracker ip info

The tracker even captured an HTTP login page for the C2 panel. The interface is entirely in Russian, so it is reasonable to assume a Russian-speaking origin.

ip info
c2 login page

Strings Analysis

Now that we understand the basic nature of the infection, we search for strings in the memory dump that mention the word β€œstealer”:

bash$ > strings MemoryDump.mem | grep -ai stealer

keyword search in malware with strings

We find references to RedLine Stealer, a well-known and widely sold malware. RedLine is commonly bought on underground markets. It comes either as a one-time purchase or as a monthly subscription. This malware collects browser passwords, auto-fill data, credit card information, and sometimes even cryptocurrency wallets. It also takes an inventory of the system, gathering information about hardware, software, security tools, and user details. More advanced versions can upload or download files, run commands, and report regularly to the attacker.

We can also use strings to search for URLs where the malware may have uploaded stolen data.

finding urls in malware with strings

Several directories appear, and these could be the locations where the stolen credentials were being stored.

Timeline

Tammam wanted to download a VPN tool and came across what looked like an installer. When he launched it, the application behaved strangely, but by then the infection had already begun. The malware injected malicious code, and used rundll32.exe to run parts of its payload. Tun2socks.exe and Outline.exe helped the malware hide its communication by routing traffic through a SOCKS proxy, which allowed it to connect safely to the attacker’s C2 server at 77.91.124.20. From there, the stealer collected browser data, captured user inputs, and prepared to upload stolen credentials to remote directories. The entire activity was visible inside the memory dump we analyzed.

Summary

Stealers are small but very dangerous pieces of malware designed to quietly collect passwords, cookies, autofill data, and other personal information. Instead of causing loud damage, they focus on moving fast and staying hidden. Many rely on trusted Windows processes or proxy tools to disguise their activity, and they often store most of their traces only in memory, which is why memory forensics is so important when investigating them. Most popular stealers, like RedLine or Amadey, are sold on underground markets as ready-made kits, complete with simple dashboards and subscription models. Their goal is always the same.

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