In the shadowy corners of the internet, a new arms race is escalating, and the weapon of choice is artificial intelligence. We’re joined by Dominic Jainy, a leading expert in AI and machine learning, to dissect a troubling development: an AI-powered malware service known as “InternalWhisper.” This tool, advertised on dark web forums, claims to make malicious code completely undetectable by rewriting it with every single build. Our conversation will explore how this AI-driven metamorphic engine is a significant leap beyond older evasion techniques, how its user-friendly web panel is democratizing cybercrime, and the layered stealth tactics it employs to bypass even advanced security like Windows Defender. We will also examine the “Malware-as-a-Service” business model that fuels its continuous evolution and what organizations must do to defend against this next-generation threat.
The report highlights an AI-driven metamorphic engine that rewrites code with each build. How does this AI approach fundamentally differ from older polymorphic techniques, and could you detail the step-by-step process an attacker uses to generate a unique, signature-less binary with this tool?
The difference is night and day. Older polymorphic techniques were like a criminal changing their coat and hat after every crime; the underlying person, or code structure, was largely the same, just with a different encryption layer or packer. This AI-driven metamorphic engine is far more profound. It’s like having a completely new person commit each crime. The AI doesn’t just obscure the code; it fundamentally rewrites its logic, reorders functions, and generates functionally equivalent but structurally unique binaries from the ground up. For an attacker, the process is disturbingly simple. They log into a web panel, upload their malicious payload—say, a C++ binary—choose their desired stealth options from a menu, and click a button. In seconds, the AI engine gets to work, recompiling the code into a brand-new, signature-less executable that has never been seen before.
The service operates via an automated web panel, lowering the technical bar for users. Based on your experience, how does this “democratization” of evasion tools change the threat landscape, and what types of less-skilled actors can now execute attacks that were previously out of reach?
This is one of the most concerning aspects. It effectively puts a weapon of mass disruption into the hands of the masses. Previously, crafting malware that could reliably bypass modern endpoint detection required deep expertise in reverse engineering, assembly language, and operating system internals—the domain of sophisticated, well-funded threat groups. Now, that barrier to entry has been obliterated. With an automated web panel, a low-skilled actor, perhaps a disgruntled employee or a novice cybercriminal, can create a piece of malware with evasion capabilities that could rival a state-sponsored tool. This means we’re going to see a flood of highly evasive threats used for more common crimes like data theft or small-scale ransomware, attacks that were previously easier to stop. The threat landscape becomes much noisier and far more dangerous for everyone.
The threat actor advertises stealthy loader options like direct system calls and process hollowing. Could you explain the mechanics of these techniques and share a real-world example of how they work with AES-256 encryption to bypass modern endpoint security solutions like Windows Defender?
It’s a masterful combination of layered deception. First, the core malicious payload is encrypted with a strong algorithm like AES-256, making it look like random, harmless data to any static scanner looking at the file on disk. When the malware is executed, the loader’s job is to invisibly decrypt and run this payload. To do this, it avoids standard, heavily monitored Windows functions. Instead of making a normal API call, it uses direct system calls, which is like bypassing the building’s front desk security and speaking directly to the system’s core, the kernel. This is incredibly difficult for many security tools to monitor. Then, it uses a technique like process hollowing. The loader will find a legitimate, trusted process that’s already running—like your web browser or a Windows service—hollow out its memory, and inject the now-decrypted malicious code inside. To Windows Defender, it just looks like a trusted application is running as expected, but it’s secretly a Trojan horse executing the attacker’s commands.
This crypter is offered with tiered pricing plans, like a legitimate business. What does this “Malware-as-a-Service” model tell us about the operator’s long-term goals, and how does this sustained development model create a more persistent challenge for security teams versus traditional one-off malware?
The business model tells us everything about their intentions. This isn’t a one-and-done tool created by a lone wolf. The tiered pricing, the web panel, the alias “ImpactSolutions”—it all points to a professional, commercially driven operation. Their goal is to build a sustainable, profitable business by selling cybercrime capabilities. This is far more dangerous than a static piece of malware. A traditional tool, once discovered and fingerprinted by security vendors, is effectively neutralized. But with a service model, the developers are incentivized by subscription fees to constantly update and improve their product. When defenders find a way to detect one version of “InternalWhisper,” the developers will already be rolling out a new build with enhanced features, creating a relentless cycle that keeps security teams permanently on the back foot.
Given that “InternalWhisper” is designed to make malware “fully undetectable” against static analysis, what specific, next-generation defensive strategies should organizations prioritize? Can you outline a few practical steps security teams can take to improve their chances of detecting these threats at runtime?
Static analysis is essentially dead in the water against this kind of threat. You can’t rely on file signatures when the file is different every time. The focus must pivot entirely to runtime behavior and anomaly detection. First, organizations need to invest in Endpoint Detection and Response (EDR) tools that don’t just look at files but deeply monitor process behavior. A key step is to baseline what’s normal in your environment. For example, a Microsoft-signed process should not be making direct system calls to allocate executable memory or initiating strange network connections to an unknown server. Second, memory forensics becomes critical. Security teams need the ability to scan the memory of running processes to spot the signs of code injection from techniques like process hollowing. Finally, assume a breach will happen. Implement strict network egress filtering. Even if the malware gets in and executes, you can often block its ability to communicate with its command-and-control server, effectively neutering it.
What is your forecast for the role of AI in both malware development and cybersecurity defense over the next three to five years?
We are standing at the precipice of an AI-driven arms race in cybersecurity. On the offensive side, what we’re seeing with “InternalWhisper” is just the beginning. In the next few years, we’ll see AI not just creating evasive code but also autonomously discovering zero-day vulnerabilities, crafting hyper-realistic phishing campaigns tailored to individuals, and even managing attack infrastructures. In response, defense will become completely reliant on AI. Human analysts simply cannot keep up with the speed and scale. We will see defensive AI that can predict attacks based on precursor activity, hunt for threats with behavioral analytics that far exceed human intuition, and orchestrate automated responses that can isolate a compromised system in milliseconds. The cybersecurity landscape will become a battlefield of competing AI systems, where victory is measured in microseconds.