Two Apple Silicon chip flaws could expose your private data to thieves
Apple's processors are fast because they predict what you'll need next, but when they guess wrong hackers can exploit those mistakes to steal your private data.

M3 MacBook Pro
, like the M2 and M3, is designed to be some of the fastest in the world, powering iPads and Macs. Their strength is speculative execution, a feature that guesses what you'll need next to keep things running smoothly.
But new research shows this speed boost comes with a cost. When these guesses are wrong, they can create vulnerabilities that hackers could use to access sensitive information, like emails and credit card details.
SLAP & FLOP attacks
Researchers from the Georgia Institute of Technology have identified two new Apple Silicon security vulnerabilities in Apple's recent CPUs, named SLAP and FLOP. These attacks exploit features in the M2, M3, A15, and A17 chips that are supposed to improve performance.
The problem lies in how Apple's processors try to predict memory operations to speed up tasks. When these guesses are wrong, they accidentally open the door for hackers.
SLAP (speculative execution via Load Address Prediction) lets attackers access private data, like email content, by tricking the processor into using out-of-bounds memory. FLOP (False Load Output Prediction) goes even further, bypassing memory safety checks.
These aren't just theoretical attacks. The team demonstrated how SLAP could extract private emails from Safari and how FLOP could recover sensitive data like credit card details.
While there's no evidence of hackers exploiting these flaws in the wild yet, the potential is there.
Apple's next move
SLAP and FLOP are similar to other speculative execution attacks like Spectre and Meltdown, which caused widespread concerns a few years ago. The difference here is that they specifically target Apple's hardware.

SLAP and FLOP. Image credit: Georgia Institute of Technology
Apple hasn't yet released a fix, but it's aware of the Apple Silicon vulnerabilities. The researchers who found SLAP and FLOP notified Apple about a year ago for one flaw, and about six months ago for the other.
However the M4 chip was well underway at that time. True fixes often require changes at the chip level, which can't happen until the next generation of processors.
Software updates might mitigate the problem.
What you can do to stay safe
If your Mac, iPhone, or iPad uses an M2, M3, A15, or A17 chip, it's vulnerable. That includes devices like the M2 MacBook Air, the iPhone 15 Pro, and the latest iPads. Older devices with M1 or earlier chips aren't impacted by these particular vulnerabilities, though they might face different risks.
Keep your devices updated with the latest software, including security patches. Avoid untrusted websites and disable JavaScript when not needed. Browser extensions that block scripts can also help.
Read on AppleInsider
Comments
from https://predictors.fail/
I suppose you're trying to present this in more broadly relatable terms, but to describe speculative execution as "guessing" is oversimplification. If you look up the word guessing you'll find something to the effect of "an estimate or supposition based on a lack of sufficient information." This does not apply to any of the performance optimization techniques and algorithms developed and implemented since the dawn of digital computing.
The architectural fundamentals for how most digital computers work were developed early. Even then it was important to optimize those computers to best utilize the available resources provided by the underlying hardware. Soon thereafter when computers were actually put to work using programming languages (software in some form) it became very evident through observations, measurements, and statistical and probabilistic analysis that there were many additional ways to optimize both the hardware and software to get better performance and utilization.
Said in simpler terms, once they started using computers they were able to observe and identify where the bottlenecks were and took steps to mitigate the bottlenecks that were found. Applying the theory of constraints, when the biggest bottleneck was squashed or reduced, another bottleneck rose to the top of the list and became the next target to mitigate. Rather, rinse, and repeat, This process has continued to this day. However, this has never been a whack-a-mole reaction because computer architects, engineers, and scientists gained much more understanding of how different design approaches led to bottlenecks and inefficiencies in the first place, some of which are constrained by the current fundamental architecture (Von Neumann architecture) of modern digital computers. Going after these challenges required the application of some very heavy mathematics.
The mathematical basis and proofs for many of the hardware and software optimizations that have been introduced in the past few decades is solidly grounded in statistics, probability, set theory, prediction, physics, material science, etc. The mathematical core of engineering education used to be grounded mostly in algebra, calculus, differential equations, linear algebra, thermodynamics, electromagnetic theory, etc. It still is. Since the advent of digital computing and computer science the mathematical grounding now includes probability, statistics, set theory, queuing theory, algorithms. data science, etc. This emphasis on probability and statistics has grown massively as computer engineering and computer science has advanced. It is no more evident than it is for the advancement of AI. The computer engineers and architects that design Apple's SoCs have to be firmly grounded in all of the above mathematical disciplines. But as we see here with SLAP and FLOP, they can and occasionally do still make mistakes.
There is no guessing going on.