By KiddieDaily Editors · 2026-06-29 · 3 min read · 1 source

To study how chips really work, MIT researchers built their own operating system

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Close Breadcrumb MIT News To study how chips really work, MIT researchers built their own operating system To study how chips really work, MIT researchers built their own operating system A new kernel called Fractal gives researchers a cleaner view of what’s happening inside a processor, and has already surfaced previously unknown behavior in Apple’s M1. Rachel Gordon | MIT CSAIL Publication Date: June 10, 2026 Press Inquiries Press Contact: Rachel Gordon Email: rachelg@csail.mit.edu Phone: 617-258-0675 MIT Computer Science and Artificial Intelligence Laboratory Close Caption: Fractal relies on a new construct: the outer kernel thread, which sits inside a user process’s memory but executes with kernel privileges. “If you’ve got a hand magnifying glass, you can see a little bit.

But if you had an electron microscope, now we’re really talking. The electron microscope of operating systems,” says lead author and MIT PhD student Joseph Ravichandran. Credits: Image: Gabriel Maragaño Previous image Next image A new kernel, or core program within an operating system, gives researchers a cleaner view of what’s happening inside a processor.

Called Fractal and developed at MIT, the kernel has already surfaced previously unknown behavior in Apple’s M1. When security researchers want to understand what a modern processor is really doing with the kind of detail that determines whether attacks like Spectre and Meltdown are possible, they usually run their experiments on top of an operating system that was never built for the job. They open up macOS or Linux, patch the kernel by hand, and hope the modifications hold.

The approach is unstable, hard to reproduce, and on Apple’s platforms, slated for deprecation. A team at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) decided to build something different. Fractal, an operating system kernel written from the ground up, treats the hardware itself as the object of study.

Its first major use, a deep look at branch predictors — a CPU’s way of guessing what code to run next, before it knows for certain, so it doesn’t have to waste time waiting to find out — inside Apple’s M1 processor, has already turned up findings that prior work missed, including the first evidence that a class of speculative attack known as “Phantom” affects Apple Silicon. “We’re using hardware in ways it wasn’t designed for,” says Joseph Ravichandran, the MIT PhD student in electrical engineering and computer science (EECS) who led the project. “It’s not even obvious that this is a possible thing you could do with the hardware.

But we found a way to pull all these different primitives off. If you’ve got a hand magnifying glass, you can see a little bit. But if you had an electron microscope, now we’re really talking.

The electron microscope of operating systems.” The core problem Fractal solves is one that researchers have worked around for years. Modern processors keep state in many internal structures: branch predictors, caches, translation lookaside buffers, and more. To study how those structures behave across the boundary between user code and kernel code, two domains the chip is supposed to keep isolated, researchers need to run nearly identical experiments on each side of that boundary.

On a general-purpose operating system, that is very difficult. The system itself manages privilege levels, address spaces, and scheduling, and it injects its own activity into every measurement. Fractal inverts the model.

It boots directly on bare metal, with no other software running, and exposes primitives that let a single experiment switch privilege levels at runtime while executing the same instructions in the same address space. The team calls the underlying technique multi-privilege concurrency, and it relies on a new construct they introduced: the outer kernel thread, which sits inside a user process’s memory but executes with kernel privileges. The result is an experimental setup with almost no background noise.

Where measurements taken under macOS or Linux are blurred by interrupts, scheduler activity, and address-space management, Fractal produces flat baselines and clean signals.

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