What is the malware family Qbot?
Qbot (also known as Qakbot, Quakbot, and Pinkslipbot) is a banking Trojan and stealer malware in circulation for over a decade. It is typically delivered through phishing techniques to get users to open malicious attachments or to lure victims onto phony websites that use exploits to execute Qbot onto a victim’s machine.
Once it has established a foothold, Qbot can employ various malicious behavior, including keylogging, cookie exfiltration, and process hooking. It has also been used to drop backdoors onto compromised systems and deliver wider-reaching, targeted ransomware attacks against banking networks.
A brief history of Qbot malware and its evolution over time
Qbot is a type of information stealer that has been around since 2007. Over the years, Qbot has evolved significantly, with new variants appearing regularly.
One of the most significant changes to Qbot came in 2016 when a new version of the malware emerged that included worm-like propagation capabilities. This new functionality allowed Qbot to spread more quickly and efficiently across networks, making it an even greater threat to organizations.
In recent years, Qbot has continued to evolve and adapt. Some malware versions have included capabilities for stealing login credentials from web browsers and email clients. Others have focused on stealing sensitive data from infected systems or using compromised machines as part of larger botnets.
Despite efforts by law enforcement and cybersecurity researchers to disrupt Qbot’s operations, the malware remains a significant threat today. Its ability to evade detection and continually adapt to new security measures makes it a challenging adversary for organizations looking to protect their systems and data.
What are the common methods used by Qbot to spread and infect systems?
Qbot malware is modular, and its functionality has varied since it was discovered over a decade ago. Although it began strictly as a banking trojan, it has since evolved to become a “Swiss army knife” for cybercriminals. It is frequently loaded with specific functionality tailored to accomplish particular goals.
How is Qbot Distributed?
Qbot variants have even been distributed by other loaders, such as Emotet, as part of large-scale malspam campaigns. Some common modules that have been included in recent iterations of Qbot include email collectors used to steal email threads from Microsoft Outlook, hooking modules to inject phony web forms into browsing sessions, dedicated password stealers, cookie grabbers, and plug-ins that facilitate the opening of remote desktop sessions on the victim’s computer.
What is Qbot’s Execution Flow?
Upon its initial execution (generally when a victim opens a Word document with an embedded VBA macro that arrives as part of a targeted phishing attack), Qbot attempts to evade detection by performing multiple checks for the existence of virtual machines or malware sandboxes. It will then typically sleep for a randomized amount of time (another commonly-employed context-aware evasion technique).
When Qbot wakes, it initializes a secondary execution by installing itself into the application folder’s default location and then making a copy of itself in the registry key HKCU\Software\ Microsoft\Windows\CurrentVersion\Run to ensure its persistence after the system reboots. Qbot then executes the copy of itself in the default application location and replaces the initial infected file with a legitimate one. Finally, Qbot creates an explorer.exe process that updates Qbot periodically from a remote command-and-control server and executes malicious modules.
Variants of Qbot malware and their capabilities
Qbot has undergone several evolutions, with new variants appearing regularly. Each variant has unique features and capabilities, making it more potent than the previous version. Here are some of the different variants of Qbot malware:
Version 1
The first known version of Qbot, discovered in 2009, was a simple banking Trojan that primarily targeted financial institutions. It would steal login credentials and other sensitive data inputted by users on infected systems.
Version 2
The second version of Qbot, discovered in 2010, saw the introduction of keylogging capabilities. This allowed the malware to record user keystrokes on infected systems, giving cybercriminals access to even more sensitive information.
Version 3
Version three of Qbot emerged in 2013 and significantly changed the malware’s codebase. This version included new anti-detection techniques that allowed it to evade detection by antivirus software and other security measures.
Version 4
In 2016, a new variant of Qbot emerged that included worm-like propagation capabilities. This version could spread across networks more quickly and efficiently than previous versions, making it an even greater threat to organizations.
Version 5
The latest known variant of Qbot is version five, first identified in late 2020. This version includes several new features, such as stealing data from virtual machines and using compromised machines as part of larger botnets for carrying out additional attacks.
As Qbot continues to evolve, organizations need to stay up-to-date on the latest threats and take proactive measures to protect their systems and data from this dangerous malware family.
What are Qbot’s Evasion Techniques?
Qbot is known for its sophisticated evasion techniques, which allow it to evade detection by security solutions and remain hidden on infected systems for extended periods. One of the most common tactics Qbot uses is code obfuscation, which involves modifying the malware’s code to make it more challenging to analyze and detect.
Another technique Qbot uses is anti-analysis measures that can detect when the malware is running in a sandbox environment. When these conditions are detected, Qbot often shuts down or changes its behavior to avoid detection.
In addition to these techniques, Qbot has also been known to use fileless infection methods that can evade traditional antivirus software. This involves injecting malicious code directly into a system’s memory rather than writing it to disk, making it more challenging to detect and remove.
Overall, Qbot’s sophisticated evasion techniques make it a formidable adversary for organizations looking to protect their systems and data from this dangerous malware family. Organizations must employ advanced endpoint security solutions to detect and block malicious activity in real time while implementing robust security policies and user education programs to combat these threats effectively.
How to Analyze Qbot
Analyzing Qbot can be complex, but it’s possible to identify and detect this malware family with the right tools and techniques. One such tool is VMRay, which provides advanced threat detection capabilities to help organizations avoid evolving threats like Qbot.
To analyze Qbot using VMRay, upload a file containing the malware to the platform. Once uploaded, VMRay will automatically begin its analysis process, which involves running the malware in a virtual environment to observe its behavior and gather information about its capabilities.
During the analysis process, VMRay generates various artifacts that can be used to identify and detect Qbot. These artifacts include dynamically extracted function call strings, user agent strings, IP addresses, process names, and command lines.
Organizations can create custom detection rules by incorporating these artifacts into SIGMA or YARA rules to help identify Qbot on their systems. These rules can be used alongside other security tools like endpoint detection and response solutions to provide comprehensive protection against this dangerous malware family.
Overall, analyzing Qbot requires a combination of advanced threat detection tools and techniques. By staying up-to-date on the latest threats and taking proactive measures to protect their systems and data from malware like Qbot, organizations can reduce their risk of falling victim to cyber-attacks.
Sample Qbot Malware Analysis Reports:
https://www.vmray.com/analyses/_mb/b8e5e6f25a38/report/overview.html
https://www.vmray.com/analyses/_mb/f0fc0e170029/report/overview.html
https://www.vmray.com/analyses/_mb/2200463f3dec/report/overview.html
https://www.vmray.com/analyses/_mb/696156d9a411/report/overview.html
https://www.vmray.com/analyses/_mb/286512f7ef23/report/overview.html
https://www.vmray.com/analyses/_mb/d2c969098c9a/report/overview.html
https://www.vmray.com/analyses/_mb/286512f7ef23/report/overview.html
