RE: https://infosec.exchange/@wdormann/117000612920568052
I'm not a big fan of takes like "the research by Anthropic is just marketing because they only attacked a reduced round AES implementation." (Quoted toot is just one example, I've seen it in several other places).
Attacking reduced round implementations is standard fare in cryptographic research, and valuable on its own, as it can teach us things about which approaches might be valuable in attacking AES with more rounds. Saying "this result doesn't matter / is just marketing because it doesn't break full-round AES" also says that 20 years of academic research into reduced round AES does not matter, which is obviously bonkers.
I am not saying that the Anthropic results are groundbreaking (Matthew Green has a much more detailed take and a lot more background in this than I have). But I *am* saying that I dislike the pracice of dismissing any research done by AI labs just because it was done by an AI lab. The other attack actually led to an algorithm being removed from consideration in the PQ crypto competition, and even though some people say "well, it's just applying a known weakness", this apparently wasn't enough to disqualify it until now.
Or, to quote Matthew Greens article:
> If you’re under the impression that these models are “glorified autocomplete” or that progress is slowing down, I need to urge you: stop thinking that. The models are very intelligent and capable, they are getting better at a fast clip. I can cite measurable and impressive progress over just the past five months on specific types of problem I’ve asked them to look at. If there’s a ceiling out there, I don’t yet see evidence of it. The people who think models are dumb are mostly using Google’s free AI search results, and not interacting with the high-end stuff (which only costs $20, so it’s not out of reach.) And they’re mostly not working in new areas.
https://blog.cryptographyengineering.com/2026/07/29/some-notes-about-anthropics-new-results/