12 - Network State Conference 2026 - Will AI Break Cryptography?

uh preemptively I will be running off for a flight before this panel ends. So I'm going to uh hand off moderator responsibilities to hib for the end. But to get us off kicked off, we had a tweet that rocketed around the world last night from Justin Drake uh telling everyone to not panic. Um >> of course they panicked. >> Of course they panicked. And this is about uh the correctness the the validity of cryptography and math. Um and I do want to talk about crypto in the longer term but now because people are panicking I think we need to talk about math and cryptography in the short term. Uh the fear is that AI has truly accelerated timelines on a massive scale to compress uh tricks uh shortcuts to break classical cryptography and then also accelerate the arrival of Qday as well. Uh the day that quantum computers can break uh cryptography as well. So, two different paths to breaking down the entire foundation of what the blockchain industry rests upon. Uh, Hib, you've already written an article. I'm wondering if you can kind of just give me your first impressions, your first thoughts to to this fear about AI threatening the entire industry. >> Yeah. So, I I made the analogy that this has sort of become cryptographic dumerism. Uh it's a sphere that like if if you look at most of the cryptography that we use today uh we don't actually have any proofs that this cryptography is sound. Uh the the way that we battle test cryptography is we create new cryptographic schemes and we get a bunch of smart people cryptographers to look at these schemes and say like hey can you come up with a way to break this and after enough time after enough people after enough years if people don't find ways to break it then we say well this is probably pretty strong cryptography. Uh that that said cryptography does degrade over time people do find attacks they find ways to weaken a given protocol. Um but we sort of measure the security of most of our cryptography not in terms of formal mathematical guarantees which we don't have but rather in terms of the person hours the the sort of the the the mathematical intelligence that we have applied to these problems and haven't found a way to break them. Well, if that's true, then if you have Open AI now pointing their lasers at classical cryptography, it may well be that all of the human cryptographers in the world, which is maybe around 10,000 at most, have applied this much intelligence and compute to looking at all the cryptography we have. And it could be that over the next month, we apply this much compute to all the cryptography in the world. in which case we may just be totally unprepared for how many holes exist in the foundations of classical cryptography. I think that point is correct. That said, the question is what are you going to do about it? If the answer is what Justin Drake advocated for, which is what he calls bunker mode and bunker mode, the idea is don't move. Move all your coins to an address that has never signed anything. Put your head in the sand and like basically, you know, buy or use a blockchain. >> Exactly. But, you know, buy buy a villa in New Zealand and like escape from society because you just don't know. It might be a smoking crater when you're done. That is a bad answer. >> That is the equivalent of doomerism which is like, "Oh my god, you know, AI is going to kill everyone. So, just like, you know, take no thought for tomorrow and uh, you know, abandon your family." I I this I think is the is is the wrong answer to a correct observation. Mhm. >> So what what I advocated for in this post is that every blockchain needs to basically think of creating a cryptographic recovery mode which is a way that validators upon seeing >> this what we were talking about yesterday. >> Exactly. Exactly. Upon seeing that there is some kind of foundational problem in cryptography that you can fall back to like cold war level extremely austere cryptography that makes minimal assumptions. um basically like you know this kind of hashbased cryptography which is very slow, very expensive, gigantic signatures, terrible bandwidth, right? Blockchains would run at the speed of molasses, but we know that we're safe. >> Mhm. >> Like this is kind of like, okay, nuclear codes went off. The the sirens are are we all go into the bunker and we can figure out what do we do now? What's our next move to reconstruct once we know what have been the problems that are uncovered in cryptography? What cryptographic solutions are safe? And we'll probably actually learn a lot more if AI is pointing. >> AI will also help us develop methods and pro and potentially prove the things we couldn't prove before. >> Exactly. Exactly. >> You know, so go ahead. Say that. I was going to say >> no. No. So that that's basically the proposal that I came up with which is that >> so this what we're talking about yesterday that's a um very similar is like I if you have a existing pre-existing social smart contract or coin holder agreement or DAO which says under the conditions where there is some new mathematical discovery that invalidates this then we've all pre-aggreed to maybe rewind state you know to to two weeks ago everybody does lose money but they lose less money than zero or that this this and this developer have emergency authority that we can turn the keys and they can upgrade these functions or whatever. Um, the thing I find most interesting on this whole thing, the the math singularity was Matthew Green's observation, I know Dev was arguing about this, that public key cryptography may not work, you know. And by the way, the other thing that's funny about this, there's been no coverage of this in like the New York Times. They have salsberers guys have no concept of how to even report on this or talk about this. So, and yet it influences every country in the world in terms of whether they can secure their systems. So network is just moving far ahead the state. Anyway, some thoughts I maybe your thoughts. >> Yeah, I mean I think we actually when in 2018 we're designing near one of the things we were designing for is like hey look there going to be new cryptography. We cannot bind near blockchain to a one specific cryp cryptography curve. And so we designed to be able to keep adding more different methods. And so earlier this year we just added MLDDSA which is one of the first postquantum uh kind of signatures. And you know given where world is moving we're probably going to add a hashbased signature as well so you can kind of secure uh your system but I think the broader point is like look you cannot solidify and oify things you used it in your post as well because the world is evolving really quickly we're going to keep inventing new things and so the kind of protocol needs to be able to continue evolve with that and we need tooling to evolve uh in unison as well and I think it's all it's all possible we just need to be able to be in that mode instead of saying like cool we're going to build this and then nobody touches it from here on. >> So there's something else we talked about yesterday which is the token budget for the defense department of a coin. You want >> Yeah. Well, I think um one of one of the points I want to make before we get to that part is that >> blockchains historically have been designed to be very resistant to change. Uh decentralization by its nature is a very slow institutionalized governance process. It means that in order for something to change, there needs to be a lot of buyin. There's no real way to enforce things happening quickly. And that is often considered to be a virtue of decentralized systems is that like they they are very very methodical in the way that they end up making changes over time. Um I I sort of analogize this. This is this is sort of peace time governance. If we are going into a mode of technological acceleration where the ground underneath us is going to be changing very rapidly in the midst of this kind of mathematical singularity then that is actually the wrong kind of governance for a situation which is more like wartime. M >> wartime is often when you change the the sort of civilian command structure and you say look we have to go into more command and control mode which means that we do have to delegate more authority to validators to developers for them to be able to say hey just went down and we have to react on a dime to the fact that something fundamental has changed and people are no longer secure and we you have to trust us to have the good judgment to go in and change things. >> So I'll give I'll give uh you know in the network safe book I said uh the most unpopular but important word going forward is going to be recentralization. >> Why? Because centralization, decentralization, recentralization basically means decentralization is just a tactic. It's not like a destination. It's a direction. Just like you steer left and you steer right, you know, recentralization is opposed by both the centralized guys who say, "Wait a second. if I thought you guys were, you know, why don't you keep our existing institutions? And the decentralization guy said, "Wait a second. I thought we were all anarchists. Aren't you sacrificing?" But it's uh recentralization is just finding a new piece of digital land. It's just saying we hit the fire alarm. We got out of fiat. We got out of something and now we're forming a new group. Or recentralization is we have a network governance rather than state governance. And so then you don't have to say, "Oh, we're, you know, we're doing a wrong thing." We say this is a tool that we will use in these circumstances. You don't have to apologize for it. >> Bali, I want to get your perspective on as we proceed through this tumultuous state in the world of math and cryptography. There's a little bit of a difference. There's quite a big difference in the world of crypto, the network state where the entire industry is underpinned by the math. Whereas on the state side of things with banks, with web two, the cryptography, the security, it's it's a means to an end. It's not the main arc. It's not the main thing. And so, while this uh the this threat to math truly threatens all of crypto, it's urgent for us. And on the other side of this, it's an opportunity for us to win. Whereas the the other side of the world, it's not really their core competency. It's not really their main thing. It's just uh it's a it's a an incumbrance for them. Do you think this is an opportunity for the networks state side of the world to really to really shine? >> Yes. And I actually also want to hear Ilia's thoughts on this. But one of the things taking our conversations from yesterday putting together the right now AI is an attack, right? Because you've got this math singularity, you know, we don't know how many results are going to come out and things are going to crumble. You know, things are going to break in the short run and medium run. But in the long run, um, you know, every coin actually, so you're the new moderator. Every coin has a very strong Oh, see. Oh, okay. Fine. All right. Okay. Every coin has a very strong incentive to defend itself and has a budget for that. And so the token budget for auditing every line of code and also paying mathematicians to run all this stuff that becomes the cryptographic defense department. And then you've got the attackers over here. So to your point before you said maybe there's 10,000 cryptographers in the world or whatever that number is you can roughly quantify sort of like with mining you know like hash rate what is your um you know token rate right so you what's funny is this is a circular economy the AI agents buy crypto tokens to spend and then the crypto uh you know uh protocols buy AI tokens so that you know these guys are making sure they're not hacked and these guys are proving they're So there's a circular economy of AI agents buying crypto tokens and crypto protocols buying AI tokens. I think that actually will be a significant part of the future. I mean one way to frame it is you need the protocol own compute. >> Yeah. Right. You effectly need to have I mean obviously we're coming from behind for open AI entropic uh of the world but the you know if we know anything about blockchain we can motivate people to bring a lot of compute uh up. I mean one of the things is with AI you can systematically enumerate exactly which papers your blockchain depends on. like you can literally list every single paper that ECDSA depends on that you know any any cryptographic scheme assumption depends on and those are almost like library calls in the sense of a mathematical library or an educational library and so you're attacking them as soon as a new model is posted on open router you ping it you immediately are blasting tokens at it you're trying to attack your own foundations first much as we've sort of learned to do for our JavaScript or Python dependency is you start thinking about math itself as a dependency that has a supply chain vulnerability. >> Well, it's it's interesting because I think there's an asymmetry between uh normal cyber security and what we're talking about with this math singularity. With normal cyber security, I think many people worried that okay, when models are going to become superhuman at at cyber that there's just going to be this just apocalypse of just I don't know this like sort of apocalypse now type hellscape of things getting hacked left and right. And many people have pointed out okay we now have you know GLM 5.3 which is extremely good at cyber it's open source it's uh very easily accessible by anybody and yet there is not this just you know kind of planes falling out of the sky kind of scenario that people were forecasting for quite a while that you know the reason why mythos and and Daybreak and all these programs are whitelist only not everybody can get access to these models is because of this belief that if people had access to them openly there would just be total pandemonium. We don't see that. Why don't we see that? Where are all the hacks? Um you remember last year there was um uh the CrowdStrike attack. It was it was a vulnerability. It wasn't even an attack and it just took out like half the internet. You know, air airplanes weren't moving and civil society was kind of grinding to a halt. Um the the conjecture is that the reason why we're not seeing that is that there's a natural uh balance between attack and defense with AI. is that actually um giving defenders access to the same power of AI that attackers get there is not this as some people maybe thought it might be true uh there's not an advantage to attackers uh when defenders also can spend tokens and attackers can spend tokens they cancel each other out and in fact maybe have an advantage >> because the prompts also do matter right so the angle of it it's not quite the same as hash rate because you've got angles of attack from the prompts >> I would I would I would actually uh argue that it's better than it was in the human world. And here's so here's the shape of my argument, okay? Um, in the past before we had AIS, uh, you would hire human attackers, right? So, let's say you're in North Korea, you would hire some hackers in North Korea and they would go and try to attack a protocol, right? And if you were a defender as a protocol, you have to come, you have to basically try to defend against everything North Korea can come up with. And all of North Korea's hackers are all different. They're all independent minds coming up with different ways to try to attack your protocol. But in a world where North Korea is now spending tokens, uh the thing about AIS is that AIs are much more correlated with each other than humans are correlated with each other. Like you will see this is that if you have seven AIs all trying to attack the same problem, they will come up with very similar solutions as they are iterating and spending more and more compute on the same problem. they don't paralyze in ways that are as independent as the way that humans paralyze because they're trained from very similar distributions even if they're different models. Uh whereas humans we just act very differently. We have much higher uh diversity in dispersion in the way that we come up with ideas. As a result of that, if you have 10 models, let's say North Korea and Russia and you know somebody else are all attacking you, it's very likely they will come up with the same attack ideas. And so if each of them spend a million dollars of comput and you spend $2 million of compute, it's very likely you will come up with each of the ideas their models will come up with because they're not coordinated. >> It's interesting because let's let's say that's true and it's possible um if you take the enumeration of the math papers as your library that underpins you in the same way the JavaScript and Python libraries do, then you could say, okay, I've got a finite attack surface now, right? I think for for math you have like very different level of uh like attacking math the outcome you're going to break everything right yeah like attacking a single library or system you have like its supply chain which I mean what we've seen right now people starting to remove dependencies in general in code because actually dependency is a liability now like it's easier to just write all your code from scratch from kind of as basic as possible and then audit it with a bunch of agents uh and you have formal notification now so you and actually verify that the code. And so I think actually in general the code building is becoming like completely asymmetric toward the builder because you you just want to remove all dependencies and you want to formally verify kind of as much properties as possible. With math you have effectively right now the the fundamental like okay what is the like even when we use forification we actually have set of assumptions right we say hey this is a hard problem like for example we verifying zero knowledge proofs there's a assumption in the lean proof itself that this you know this problem is hard and then from there we verify that this Zcash for example has no uh like double spend >> and [snorts] that assumption itself is what's getting banned and and indeed like then everybody as an attacker it makes sense to attack that fundamental assumption. >> Yes. >> And spend all of the kind of cost on that and you break everything, right? >> You know, you know what's funny about this? It strikes me um you know one of the phenomena of the last few decades has been previously obscure areas that only mathematicians or computer scientists cared about like formal verification then some you know or obviously you know machine learning and so on and now pure math is about to have an AI like bidding war right where those salaries I mean all the mathematicians today are depressed but in two or three years it's going to their salaries are going to 10x because >> I I don't know that that's true. I think >> let me give you my argument. >> Okay. Yeah, please. >> Basically, um the the human-guided uh I mean because you have to prompt these things, right? It's not like anybody can just prompt their way to the quasan hypothesis and you have to verify it and prompting and verifying are still skills. >> I mean if you look at the Navier Stokes story, yeah, I mean they made very clear we did not know anything about Navier Stokes. We did not. So we we're running right now. We're number one on lean bench line bench nobody read anything this is like thermma theorem reman hypothesis like this is like 120 most sophisticated papers and we've like verified them in lean we like you know we don't even know some of the names there >> I you know but still even still if you didn't comprehend what the symbols were on screen how did you even know what the lean was saying I >> well the lean lean is like actually >> I know but >> okay well you could look at the output of the program, but I I think it'd be hard without domain knowledge to even understand what one was looking at. You don't you don't think >> I mean I I think this is math code. >> You disagree with >> I think this is math code. I think it's very clear that like there's a good reason why mathematicians are despondent, which is that look, this has happened to programmers now. Programmers now realize that like my job is forever different. And like right now you need you need humans to drive the models. Um but it's very clear that the models are now driving themselves more and more. >> Yeah. But is that >> but you need the problem solving skills not like before as a mathematician your goal was like to to you given a problem and you go and like try to prove it right and you spend you know decades doing that. Now it is actually formulating the problem is the skill. >> Yeah. And this is for developers and now for mathematics too. And that is a way broader. >> Yeah. prompting and verifying. I mean, okay, I know there's a lean proof that's out there, but >> I mean, how many people know how to look at lean proofs, right? That's actually you don't actually need to look at lean proof. You only need to look at the statement and the statement is >> math is falling because it is uniquely self-verifying. >> You I know, but basically look, you can write down an equation. People can I I think you guys are over even if the number of people who can prompt these things has increased and let's even say it increased by an order of magnitude. >> Yeah. I mean, how many people can type in Navia Stokes with the Nablas and, you know, so on, [laughter] right? It's >> read read Scott Arensson on this. Go ahead. Um, Scott Erensson, well known quantum physicist. >> I was actually just thinking about the complexity zoo guy, right? >> Um, >> yeah, he's he's a complexity. >> Yes. Yeah. Complexity theory. Yeah. Yeah. And complexity classes. >> Maybe before we finish, we should like reinsure people uh about the crypto side. >> Okay. I know. Like >> we're up on so maybe we should just give a small thing. Uh, look, I do think what we're talking about this this cryptographic singularity, um, most likely with with, you know, 95% plus probability, what we're going to find when AIs do work their way through all this math is that, hey guys, you were right. Cryptography works overwhelmingly likely and even with most of the equations that they've se uh, OpenAI came through in the in the big paper drop they had earlier this week, what they found was that like yeah, most of the things are what mathematicians thought. There were very few surprises in the sense that like oh something we thought was true was false or something we thought was false was true. So most likely what we will find is that we're like yes >> that's interesting. I hadn't seen that. So there's a 2x2 table of things they thought were false that were false like that's a useful >> the Jacobian the Jacobian conjecture that was surprising. We did not think that there would be a counter example, right? That was very surprising. Um but for a lot of these things it's like yeah of course they just we didn't have the proof. We didn't have uh people thought the answer was yes and the answer was yes. But now we have a formalization. >> You know all these guys like Scott Aronson who look at the complexity of different you know kinds of algorithms. I think what we have to do is just try to only work with those things that have proven complexity results as opposed to those things which have conjectured difficulties. And I know that's easier to say than it than it is, but because one thing I think Justin Drake was talking about this, which is hashes are reliable and public key, you know, like a like a elliptic curves aren't. And then Dev had a counter argument on that. What are what are your thoughts on that, Elliot? Yeah, I mean I think kind of the principle is the hashbased cryptography is way like there's less of things there and so it's like way simpler and so it is more reliable and to's point like if we do need a recovery mode that is our backup and we should have this backup available for everyone at the same time it's extremely slow it's extremely inefficient uh and you know yeah you don't want to have you know high performance blockchains relying on that at the same time we do have now latisbased cryptography that is postquantum um that is actually what's used now across the internet right your browsers and we were just checking some of the like uh some of the implementation across TLS and other places and indeed it is a conjecture too right there's like hey this mathematical problem of you know matrix multiplication now is hard the benefit is if that's solved we also like AI will become way way simpler because it's the same operation underneath and so I think there's like a lot more um kind of room we have. But that's why like yeah, we cannot oify cryptography. We'll need to continue continue innovating here. But >> for right now, we're fine. And you know, like people who are working in the space are all really on top of this and really continue innovating to make sure to be ahead of it. Okay, >> good. Let's wrap. We got a wrap. Yeah. But uh thank you everybody and um cryptography is going to be okay.