Bruised but Not Broken: The Resurgence of the Emotet Botnet Malware

We also discovered that the recent Emotet samples employ LNK (link) files to download 64-bit loaders (Figure 9). These allow Emotet to directly execute PowerShell commands for payload execution. For each infection, the LNK file creates a PS1 file via PowerShell, which is then used to download and run Emotet’s payload (Figures 10 and 11).

Figure 9. Emotet’s malicious LNK file

Figure 10. The executed command from Emotet’s malicious LNK file

Figure 11. The deobfuscated command from Emotet’s malicious LNK file (Figure 10)

Another notable behavior we observed in the samples of these new Emotet variants was their use of hexadecimal (Figure 12) and octal (Figure 13) representations of the IP addresses they connected to, as we reported in a previous blog entry. Using these formats to obscure the URLs enables these new variants to circumvent pattern-matching detection methods, thereby allowing the execution of their download routines.

Figure 12. A hex representation of the Emotet URL (with carets)

Figure 13. An octal representation of the Emotet URL (with carets)

Emotet’s payload

Emotet’s older 32-bit variants use seven core commands. But the recent Emotet samples are of 32-bit variants that use only six core commands and 64-bit variants that use only five, as shown in Table 1.

Note: {installation folder} could be %AppDataLocal%{random} (non-admin) or %System% {random} (admin), depending on the mode of execution.
Table 1. A list of core commands used by the newer Emotet samples

Our analysis of the recent samples showed that Emotet’s use of rundll32.exe for execution between November 2021 and January 2022 had been phased out, replaced by the “regsvr32.exe /s” command as of February 2022. Nonetheless, Emotet employs modular architecture for its other payloads. Based on this, we can still infer that the samples have the same infection chain as in previous Emotet-related campaigns, with some variants opting to include the gathering of running processes as part of their modules instead of their main routine (Figure 14).

Figure 14. Emotet’s infection chain

The reappearance of Emotet is also notable because its operators have since added Cobalt Strike, a well-known penetration-testing tool, to its arsenal. This poses a bigger risk for target enterprises, as the integration of Cobalt Strike provides more flexibility for Emotet’s MaaS partners to gain a foothold in an intended victim’s systems. With these new features, we expect to see in the coming months a continuous stream of Emotet cases and the delivery of other malware used in Emotet’s MaaS scheme.

Similarities with QakBot

Since January, we have received and analyzed 300 submissions of the QakBot loader (Figure 15), and our investigation has revealed that its attack chain shares many similarities with that of Emotet (Figure 16).

Figure 15. Emotet and QakBot submissions from January to April 2022

Figure 16. A comparison of QakBot and Emotet’s attack chains

QakBot spam messages attempt to deceive their intended victim into clicking a download link, which is usually a OneDrive URL (Figure 17). An Emotet spam message, on the other hand, poses as a forwarded email that has a password-protected archive attachment (Figure 18).

Figure 17. A QakBot spam message containing a malicious download link

Figure 18. An Emotet spam message containing a password-protected archive attachment

QakBot infections start with the intended victim downloading a malicious Excel file with an .xlsb file name extension (Figure 19). Emotet infections also involve an Excel file, but with an .xlsm file name extension (Figure 20).

Figure 19. The malicious Excel file in a QakBot attack

Figure 20. The malicious Excel file in an Emotet attack

Another key difference between the two pieces of malware is that the macro sheets embedded in QakBot’s downloader samples contain links with the .png file name extension in the URLs (Figure 21), while Emotet links do not (Figure 22). This is a means for QakBot to evade detection, as using a common file name extension like .png makes QakBot URLs less suspicious.

Figure 21. The URLs in a QakBot macro sheet

Figure 22. The URLs in an Emotet macro sheet

Although the Excel files in both QakBot (Figure 23) and Emotet (Figure 24) infections employ regsvr32.exe to execute their payloads, only QakBot drops its payload in a folder with a random five-character name that is located in the C: drive (Figure 25). Emotet, on the other hand, drops its payload in the parent directory of its downloader (Figure 26).

Figure 23. QakBot’s use of regsvr32.exe to execute its payload

Figure 24. Emotet’s use of regsvr32.exe to execute its payload

Figure 25. QakBot dropping its malicious payload in a folder in C:

Figure 26. Emotet dropping its malicious payload in a folder

Security recommendations

For enterprises to avoid falling victim to spam emails used in Emotet and QakBot campaigns, user awareness training for employees should be expanded to address email reply chain attacks. Security practices that can mitigate the risk of infection include:

• Ensuring that macros are disabled in Microsoft Office applications
• Hovering over embedded links to check the URLs before opening them 
• Being wary of unfamiliar email addresses, mismatched email addresses and sender names, and spoofed company emails, all of which are telltale signs that the sender has malicious intent
• Refraining from downloading any email attachments without verifying the sender’s identity
• Enabling advanced detection capabilities, such as predictive machine learning

Users and businesses can defend themselves against threats like Emotet using endpoint solutions such as Trend Micro’s Smart Protection Suites and Worry-Free Business Security solutions, which have behavior-monitoring capabilities that can detect malicious files, scripts, and messages, and block all related malicious URLs. The Trend Micro™ Deep Discovery™ solution also has a layer for email inspection that can protect enterprises by detecting malicious attachments and URLs.

Additional insights by Jett Paulo Bernardo, Arianne Dela Cruz, Dexter Esteves, Gerald Fernandez, Mark Marti, Ryan Pagaduan, and Louella Darlene Sevilla

Indicators of compromise (IOCs)