Welcome back, aspiring digital forensic investigators.
The malware ecosystem is vast and constantly evolving. New samples appear every day, shared across underground forums and malware repositories. Some of these threats are short-lived, while others leave a lasting mark on history. Today, we are going to analyze one of those historically significant threats called BlackEnergy. BlackEnergy is a malware family that gained global attention after being linked to large-scale cyber operations, most notably attacks against critical infrastructure. While it began as a relatively simple tool, it evolved into a sophisticated platform used in highly targeted campaigns. In this article, we will examine a memory dump from an infected Windows 7 system and use Volatility 3 to understand how BlackEnergy behaves in memory and how we can identify it during a forensic investigation.
Understanding BlackEnergy
BlackEnergy first appeared in the mid-2000s as a relatively basic DDoS bot. Early versions were used mainly to flood websites and disrupt online services. Over time, however, the malware evolved significantly. Later variants transformed BlackEnergy into a modular implant capable of espionage, sabotage, and long-term persistence. By the time it was linked to attacks against Ukrainian energy companies, BlackEnergy was an operational platform. It supported plugins for credential theft, system reconnaissance, file exfiltration, and lateral movement. One of its most destructive uses was as a delivery mechanism for KillDisk, a wiper component designed to overwrite critical system structures, erase logs, and make machines unusable. These capabilities strongly suggest the involvement of a well-resourced and organized threat actor, commonly associated in public reporting with the group known as Voodoo Bear.
Starting the Analysis
Our investigation begins with a raw memory capture from an infected Windows 7 machine. Memory analysis is especially valuable in cases like this because advanced malware often hides itself on disk but leaves traces while running.
Profile Information
Before diving into artifacts, it is always a good idea to understand the environment we are working with. The windows.info plugin gives us essential information such as the operating system version, architecture, kernel details, and system time. This context helps ensure that later findings make sense and that we interpret timestamps correctly.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.info
Process Listing
One of the first steps in memory analysis is reviewing the list of processes that were running when the memory was captured. This gives us a snapshot of system activity at that moment.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.pslist
During this step, two processes immediately stand out: rootkit.exe and DumpIt.exe. DumpIt is commonly used to acquire memory, so its presence is expected. The appearance of rootkit.exe, however, is an indicator of malicious activity and deserves closer inspection.
To gain more context, we can look at which processes had already exited and which were still running. Processes that have ended will show an exit time, while active ones usually display “N/A.”
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.pslist | grep -avi n/a
Among the terminated processes, we see rootkit.exe, cmd.exe, and others. This alone does not prove anything, but it makes us wonder how these processes were launched.
By correlating their process IDs, we can reconstruct the execution chain.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.pslist | grep -iE “1484|1960|276|964”
Although the output may look messy at first, it tells a clear story. explorer.exe launched several child processes, including cmd.exe, rootkit.exe, DumpIt.exe, and notepad.exe. This means the malicious activity was initiated through a user session, not a background service or boot-level process. Attackers often hide behind legitimate parent processes to blend in with normal system behavior, but in this case, the activity still leaves a clear forensic trail.
Code Injection Analysis
A common technique used by advanced malware is process injection. Instead of running entirely on its own, malware injects malicious code into legitimate processes to evade detection. DLL injection is especially popular because it allows attackers to run code inside trusted system binaries.
To look for signs of injection, we use the malfind plugin.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.malware.malfind
Several processes are flagged, but svchost.exe immediately draws attention due to the presence of an MZ header. The MZ signature normally appears at the beginning of Windows executable files. Finding it inside the memory of a running service process strongly suggests injected executable code.
To investigate further, we dump the suspicious memory region.
vol -f WINDOWS-ROOTKIT.raw windows.malware.malfind --dump --pid 880
VirusTotal and Malware Identification
After calculating the hash of the dumped payload, we can check it against VirusTotal. The results say the injected code belongs to BlackEnergy.
This confirms that the malware was running inside svchost.exe as an implant. Historically, BlackEnergy was used to maintain access, collect information, and deliver destructive payloads such as KillDisk. During the Ukrainian power grid attacks, this approach allowed attackers to disrupt operations while actively complicating forensic investigations.
MITRE ATT&CK classifications help further explain how BlackEnergy operated. The malware used obfuscation to hide its true functionality, masquerading to appear as legitimate software, system binary proxy execution to abuse trusted Windows components, and sandbox evasion to avoid automated analysis. It also performed registry queries and system discovery to understand the environment before sending data back to its command-and-control servers over HTTP, a technique that remains common even today.
Strings Analysis and Persistence
Running strings on the memory image shows additional clues.
bash$ > strings WINDOWS-ROOTKIT.raw
One particularly important finding is a reference to a .sys driver file, indicating that the malware persisted as a kernel driver. Driver-based persistence is more advanced than simple registry keys or scheduled tasks. It allows malware to load early during system startup and operate with high privileges, making detection and removal significantly harder.
Loaded DLL Analysis
To understand how the malware hides itself, we examine loaded modules using ldrmodules.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.ldrmodules --pid 880
The DLL msxml3r.dll does not appear as loaded, initialized, or mapped in memory according to the module lists. When all these indicators are false, it often means the malware is deliberately hiding the module from standard enumeration methods. This is a classic rootkit technique designed to evade detection.
DumpIt.exe Investigation
Finally, we examine DumpIt.exe. Dumping the process and checking its hash reveals that it is, in fact, a trojan.
bash$ > vol -f WINDOWS-ROOTKIT.raw windows.dump --pid 276
Its behavior shows a wide range of capabilities, including file manipulation, registry modification, privilege changes, service-based persistence, driver interaction, and embedded payload execution. In short, this malware component acted as a support tool, enabling persistence, system control, and interaction with low-level components.
Timeline Reconstruction
Putting all the pieces together, we can reconstruct the likely sequence of events. A user session initiated explorer.exe, which then launched command-line activity. Rootkit.exe was executed, injecting BlackEnergy into svchost.exe. The malware established persistence through a driver, hid its components using rootkit techniques, and maintained control over the system. DumpIt.exe, masquerading as a legitimate tool, further supported these activities.
Summary
In this investigation, we used Volatility to analyze a memory dump from a Windows 7 system infected with BlackEnergy. By examining running processes, code injection artifacts, loaded modules, strings, and malware behavior, we found a sophisticated implant designed for stealth and persistence. The whole case is a reminder that advanced malware often lives in memory, hides inside trusted processes, and actively works against forensic analysis.
Source: HackersArise
Source Link: https://hackers-arise.com/digital-forensics-volatility-analyzing-blackenergy/