I don't recommend anyone scramble to move their funds to new wallets today. But we should take the risks to cryptography from AI-accelerated math seriously, and minimize our exposure to not just quantum-vulnerable cryptography, but also potentially AI-vulnerable cryptography. The core new area of risk from this viewpoint is, unfortunately, ML-DSA / FHE / lattices. (and it's also another reason, along with quantum, why ECDSA might fall even faster than expected, hence the "fresh address" recommendation) So far most people have been in the mode of thinking "elliptic curves broken, hashes safe, lattices safe". But there is a good chance that the concrete security of lattices will take serious hits from the next two years of AI math. The basic threat model is: factoring is something that naively takes 2^(n/2) time, but over decades smart people have found and optimized number field sieves, and degraded that to 2^O(n^(1/3)), which is why RSA keys and signatures need to be ~400 bytes (and not 64 bytes). What if there are skeletons in the closet like that, both for elliptic curves and lattices, that we are simply not smart enough to discover - but bots soon will be? This is a major part of the reason why for the past year ethereum's lean roadmap has been going in the "hash-only" direction: no lattices, no ML-DSA, no Falcon, no lattice-based commitments inside ZK proofs, etc. Signatures in lean ethereum are all hash-based, either WOTS or SPHINCS-. For signatures and proofs, we already know how to go hash-only. The bigger challenge is for *public-key encryption* - and this goes far beyond blockchains. Secure communication, anonymizing protocols, lots of things need public-key encryption. And unfortunately there are long-standing mathematical theorems showing why public-key encryption cannot be done with hashes alone. You have to have some kind of trapdoor object that has at least one form of usable "structure" - either group theory (incl. isogenies) or lattices or code-based or potentially in the future even more newfangled and spooky things (local mixing?). But for anything that has structure, you should assume that AI will make at least some progress in breaking that structure. Here, one reasonable inference is that if you want to make something plausibly long-term secure, multiply the key sizes by 10. To me that's a very plausible world and something not at all extreme to predict. If AI will bring us 50 years of math in 2 years, then that 50 years of math may very plausibly include a "naive factoring -> GNFS" level of improvement to our ability to break lattices. In that world, lattices will still exist, but they will have to be significantly bigger to guarantee the same level of safety. And at those new larger sizes, hash-based constructions will beat lattice-based constructions on concrete efficiency in every use case where hash-based constructions are possible at all. Theoretically, of course it's possible that hashes are broken too (eg. P = NP would imply that). But I think P = NP is very unlikely. And intuitively, it's much more likely that a mathematical object has exactly no exploitable structure (like hashes are intended to), than that a mathematical object has exactly ~3 forms of exploitable structure (for elliptic curves: associativity, Schoof, pairings) and not some secret fourth form of structure we have not yet discovered that greatly degrades its security (for elliptic curves, ECDLP and pairing security). Similar for LWE, SVP, RLWE and the zoo of lattice problems. For this reason, we do not yet see any reason to worry and start padding the byte size of hashes (if we start to worry more, we would pad the round count first before doing anything to the byte size). Concrete TLDR, my own personal views: * Hash-based > lattice-based, in those situations where hash-based is possible at all * For anything lattice-based, be much more paranoid on param sizes. Remember that blockchains are only a small portion of the cryptography story; this point goes far beyond blockchains and applies to eg. access to websites, secure messaging, Tor / VPNs ... * For privacy protocols, strongly favor NOT putting encrypted notes onchain. Instead, send them offchain through some third-party mechanism. * If it's not difficult for you, keeping your funds in addresses which have not yet been used to make a transaction is a good idea. If it's easy for you, do it. **But be careful about migrations; I personally have lost more money in botched migrations than I have lost in all hacks combined**. * For multisig wallets, doing confirmations offchain is better than onchain, because this way the signatures of signer wallets do not get exposed to the public, so if ECDSA falls to AI much faster than expected, at least the multisig "gracefully degrades" to a 1-of-1 where the 1 is whoever was gathering the signatures - a much better place to be than "anyone can take the money" firefly.social/post/x/210783…

The cryptographic world computer: vitalik.eth.limo/general/202… My attempt to express in somewhat concise terms the true meaning of basically everything planned to happen to Ethereum starting from the fork after Hegota. It's really not just a blockchain anymore. It's a hybrid architecture that combines together blockchains and modern cryptography, to enable much more powerful properties. FOCIL, EIP-8288, Lean consensus, state management, formal verification, advanced mempool improvements (including privacy), and the longer-term specter of obfuscation all mentioned.

It's an increasingly common take that AI hacking means cybersecurity is doomed. I disagree. I think cybersecurity is naturally defense-favoring once people get their shit together. And anyone who continues to hold cryptocurrency (including me, ~90% of my net worth) is implicitly making that bet. Here's why I am making that bet. First, the oversimplified punchy one-line statement: If AI can prove Navier-Stokes and FLT, then AI can prove the statement "this program is secure" as a mathematical theorem. Even if the program is very complicated. Now, the nuance: (See also: vitalik.eth.limo/general/202… ) The word "secure" is hiding all kinds of skeletons in the closet in terms of what it actually means. What does it mean for Signal (the encrypted messenger) to be "secure"? The most basic definition you might think of is: no one who doesn't hold the recipient's secret key can read the contents of the message. But: * Did you remember to include _other_ critical forms of security? Can the adversary forge messages? Can the attacker prevent messages from reaching the recipient? Can they cause your client to crash by sending malformed messages? * Have you made sure that your model of the adversary includes attackers that interfere with the protocol actively and not just passively? And attackers that interfere by replaying messages to you or the recipient that either of you sent over the wire at any point earlier? * What if the adversary hacked (or _is_) the Signal server? * How did you learn which public key belongs to the recipient in the first place? What if that process was tampered with? * What if your device gets hacked at some point in the past or future - is your message still safe then? * What if your key leaks because of a bug in your operating system? Or because you got a bugged version of the Signal client? Or what if the database is corrupted? * Or the libraries, interpreter or compiler of the programming language you wrote it in? * What if your key leaks because tiny perturbations in perceptible signals generated by the hardware leak mathematical relationships that can extract the key a few hundredths of a bit at a time? * Are you hiding the *size* of the payload? Does that matter? * You're definitely not hiding the identity of the sender and the recipient, and the exact time each message was sent (think: not just time-of-day, but also time deltas between one message and the next). Is that not enough to deduce a lot of important facts about what relationships you have, and what *kinds* of conversations you are having? So ... even definitions can be over a thousand lines of code, and need deep careful thought to figure them out. Working on making definitions more human-readable is of extreme importance - it's perhaps the only "high-level language" that matters right now. But even still, even despite all of the above, for security-critical components, the definition is a much smaller attack surface than the implementation. Verifying that the definition is adequate is a much more tractable task than scanning over the code directly - and can become even more tractable with better tooling. Definitions are also _additive_: if two groups have two different definitions A and B, then, well, you can just prove that the program satisfies both A and B. Code is not additive in this way: if a program is A + B, a bug in A _or_ B can sink the whole thing. Definitions are additive. And if you can't satisfy A and B at the same time, you've isolated the most important philosophical issue for your project to spend its next few weeks grappling with. Sometimes, definitions are not much smaller than the implementation - UI components might be one example. But for many of the most critical components - message-passing protocols, sandboxes, cryptography like SNARKs and FHE - the asymmetry is real. Historically, a large class of failures with this approach have come from people only verifying a small portion of their code, that they self-declared to be the security-critical portion, and ignoring the rest - and it turns out that something in the rest of the code is security-critical too. This was reasonable back when verification was difficult and scarce. The solution today: sorry, you have to verify over literally your entire program, including database, networking, any caching layers, everything. Modern AI can do it. So it's not about "the good guys find all the vulnerabilities before the bad guys do" - that could maybe work too, after all a finite program only has a finite number of vulns, but it's riskier - it's specifically an asymmetric strategy of making code that is much more resilient in the first place. This is the kind of direction that Ethereum is going in for the next few years. There is no future for blockchains - especially blockchains with scalability and privacy - without doing this. We need to make software actually secure. And we have already made a lot of progress.