Anthropic's cryptanalysis results on HAWK and AES show AI can now understand existing cryptanalysis results, turn them into new attacks, and even extend them
A Few Thoughts on Cryptographic EngineeringMatthew Green
Anthropic’s model-evaluation and safety teams must treat the ability to read published cryptanalysis, produce attack variants, and extend them as a concrete capability to measure rather than a purely theoretical cyber risk.
Researchers and maintainers working with HAWK or AES-related implementations gain a new reason to examine whether AI can accelerate analysis of known weaknesses and attack techniques.
Second-order effects
Other frontier-model developers face pressure to test whether their systems can translate security literature into usable cryptanalytic work, not merely answer security questions.
Security teams may shift more evaluation effort toward model-assisted attack chains, where the material is public but the synthesis, adaptation, and iteration are automated.
Third-order effects
If independently replicated, the result would broaden AI security evaluation from harmful-code generation to the model’s capacity to operationalize specialist research across longer technical workflows.
The larger governance question becomes whether safeguards and access policies can distinguish legitimate security research from scalable assistance that lowers the expertise needed to develop attacks.
The trend: This is one data point in the expansion of the agentic attack surface, as frontier models move from explaining technical knowledge toward applying it iteratively in specialized security domains.
In case you missed the previous thread, I wrote up a short blog post giving my thoughts on the new Anthropic cryptanalysis results against HAWK and AES. https://blog.cryptographyengineering.co m/ ...
A lot of cryptanalysis has the form “here's an algorithm that we think might take a year on a billion-dollar cluster but we're not sure because nobody can afford to run it outside of the NSA”. So that kind of improvement is just very tough even for experts to measure.
For a lot of the big flashy public math results you've heard about, the result is a very simple (but hard to find) counterexample where you can test it by just doing some calculation. Or there's a machine-checkable proof. That doesn't fly for a lot of non-practical cryptanalysis.
Sorry, last thing I want to say and should have said above: the biggest barrier to these results is that verifying them is now the hard part. Current models will happily produce false “result slop” that takes hours for an expert to unravel. This is now the killer.
The only consolation I have is that we'll all need to figure this out together. Because if it really does become as good as all that, all of us humans will be in the same boat.
What does it mean for cryptographers? I don't know. I struggle with it. So far it's heaven, like having a smart plastic pal who's fun to be with and can talk through your problems without solving them all. I worry that pretty soon it will, and the world will be less bright.
The good news is that it could not come at a better time. Unless we live in Minicrypt, having massive cryptanalysis resources come on line just as we're beginning a major tech transition in public-key crypto is about as ideal a time as you could get.
Where I'm worried is around public key cryptography. We don't have nearly enough people doing mathematical cryptanalysis on problems like ECDLP or RSA and lattice-based crypto is (IMHO) understudied compared to the number of “hours” of cryptanalysis it's about to get.
First, HAWK is not a deployed scheme. It's related to Falcon signatures but the attack doesn't transfer. Also: AI is not the only thing breaking HAWK; some other researchers recently produced a similar result. They admit Claude's is a little better, though.
A few people have asked about the Anthropic Hawk and AES cryptanalysis results. The top-level answer is: It's very impressive. Three immediate comments on the actual results, old-school thread below.
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