diff --git "a/bitcoinplusplus/insider-edition/crashing-bitcoin-core-with-niklas-g\303\266gge-s-fuzzamoto/deepgram_2026-06-26T074523Z.json" "b/bitcoinplusplus/insider-edition/crashing-bitcoin-core-with-niklas-g\303\266gge-s-fuzzamoto/deepgram_2026-06-26T074523Z.json" new file mode 100644 index 0000000..09349c8 --- /dev/null +++ "b/bitcoinplusplus/insider-edition/crashing-bitcoin-core-with-niklas-g\303\266gge-s-fuzzamoto/deepgram_2026-06-26T074523Z.json" @@ -0,0 +1,34639 @@ +{ + "metadata": { + "transaction_key": "deprecated", + "request_id": "019f02e3-b61f-79d1-ba3a-5677678e766d", + "sha256": "6d26c7d9ae6cdc6699a5eaeaf5ee23d8549b665d0116754d10fcb3a0065d843a", + "created": "2026-06-26T07:45:05.583Z", + "duration": 1587.9053, + "channels": 1, + "models": [ + "2a000f0d-afa1-4f20-8481-94f8bc30b0b2" + ], + "model_info": { + "2a000f0d-afa1-4f20-8481-94f8bc30b0b2": { + "name": "large-whisper", + "version": "2022-12-08.0", + "arch": "whisper" + } + } + }, + "results": { + "channels": [ + { + "alternatives": [ + { + "transcript": "I mean, I can just like start blabbing about the tool and like... I mean, I think the first one is like, so I mean, it's like, Hey, I'm Nifty. You're Niklas. You work at Brink. What are you working on these days at Brink, Niklas? Yeah. So I currently mostly work on Fuzzer Moto, which is a fuzzing framework and also a fuzzing engine that I've built to specifically fuzz Bitcoin full nodes. So currently mainly Bitcoin Core, but I have and do plan on supporting other implementations as well. Like I have done some BTCD fuzzing and Libitcoin as well. And the main point of supporting all of the different ones is eventually to have differential testing between all of these implementations, because the more implementations you sort of add to the mix, the better your Oracle power in like finding bugs gets. That's cool. Okay, I'd like to hear more about that maybe in a minute because I don't know what Oracle power means, but maybe just for like, so I'm talking, I mean, I know what fuzzing is. Like I remember when Matt Corallo started doing fuzzy and lightning in like 2019, 2020, right? So like, but I think there's a lot of people even like Bitcoiners or technical Bitcoiners that don't really know what it means to do fuzzing. Do you have like a, I don't know what's to explain like a 5 version of making of what, like When someone says they're doing fuzzing, what does that even mean? I can try. So fuzzing is basically an automated and randomized testing technique for software. And the most common form that most people that have used it before will probably be familiar with is that you test individual functions in your code or maybe classes and you test the APIs of the classes. So the most well-known fuzzing engine is libFuzzer, which ships with the Clang compiler. And there's also AFL++ or HongFuzz. And all of these three engines are like general purpose fuzzing engines. And that basically means that, actually I think I kind of skipped ahead a little bit too far in explaining the tools. Okay, maybe the dumbed down idea for fuzzing is that you have a piece of code that you want to test. And then all it basically is that you have a loop that calls this piece of code that you want to test over and over again, and it'll pass randomized inputs to, let's say, the function that you want to test. And then there's a whole bunch of optimizations to make that fuzzing loop smarter. So for example, to make smarter mutations, to have better inputs to your function. There's also, which is now basically the default for all fuzzing efforts, but initially it wasn't. There is coverage-guided fuzzing, which essentially means that you will pass an input into the function you want to test, and you observe which parts of the function you reached with that input. And if you've reached something new, you'll keep the input in a set, which is typically called the corpus. And then later on, you'll pick an input from your corpus again, mutate it, pass it to the function again. If it hits something new, you add it to the corpus. If it doesn't hit something new, you just discard it and pick the next input. Or if you find something interesting, like a bug, for example, a crash, then you also report it as, hey, there's something wrong. It's kind of like, You know, there's this like, I don't know what they call it, like a thing, like if you take a million monkeys and you give them typewriters and you give them like, you know, you put them in a room, how long would it take for them to like recreate Shakespeare? Is it fair to say that fuzzing is kind of like having a bunch of monkeys in a room poking at the typewriter, but the typewriter is your program? Yes, yes, I think that is a, I mean the analogy breaks down at some point, of course, but yeah, that is a way of putting it. I think you could say maybe that the monkeys, or, yeah, no, I think that's a good way of putting it. That's an optimization that would basically translate to making the monkeys a bunch smarter, like maybe knowing pieces of the Shakespeare poem or whatever. Maybe they use a dictionary so they're showing where you can set it. Exactly. Like there is literally a concept of a dictionary where fuzzers like have certain interesting pieces of bytes that we know are interesting so the fuzzer can insert. Otherwise, if you have to guess, let's say you have to guess a sequence of eight bytes, and if the fuzzer has no knowledge of those special sequences, it'll take a long, long time to actually guess the right thing. Got it. That makes sense. Right, so you kind of help it out with pre-picks. These are some juicy byte sequences. Yeah, exactly. In the Bitcoin protocol, For example, we have for the networking messages, the type of the message is a string. And then one of those useful things you could put in your dictionary is the strings for each of the message types. Okay, yeah, that makes a lot of sense. Why is it called fuzzing? Do you know where the name, but why do they call it fuzzing? I don't know the exact origin. In my mind, it's just that you take something that exists and then you make it fuzzy, like you change it a little bit. I don't know. There's probably a better explanation for where the name comes from. I don't know the exact origin. Yeah, but so you've been working on fuzzing for how long now? Like you joined Brint and started immediately like where like fuzzing is the coolest thing ever or like how did you end up getting into a point where you're building tools like Fuzzamoto? Yeah I got really like I hadn't really used it before I started working on Bitcoin. I think there was like one instance while I was working on Firefox where, I don't know, I think I wrote some code and then one of the first tests crashed and someone came back to me, hey, can you like look at this? But yeah, I got really into it after joining Brink because I was refactoring some code and the whole point of that refactor was to add more tests. And one of the things I found in BigConcord was that there were a lot of these fuzz tests. I didn't really know a lot about it, but I wanted to learn more. So I refactored the code as planned and then also wrote a fuzz test for the code that I had refactored, sort of proving the point that you can now write better tests once you've done the refactor. And that turned out to actually find a pretty serious bug in the end. And from there on I was kind of hooked because I was like, oh, this is great. And then I went down the whole rabbit hole and now this is pretty much all I do. Funny. So let's talk about Fuzzamoto, which is the project that you spend most of your time on. You said that you use it to test full node implementation, so this means you have to build the project and then you run Fuzzamoto against the binary of Bitcoin core? Yeah, so this tool is, it's like the approach is a bit different from like the typical fuzzing you will see because it's not targeting like a specific function or some like API of a class or something in the code, it's actually fuzzing the whole full node daemon. The idea is to actually use the daemon as close as possible to the production binary that we ship. But there are a few tweaks we have to make to actually enable us to efficiently fuzz it. But yeah, basically the idea is that you build Bitcoin Core as close as possible to the production setup. And then you give it to the father and it'll like, use the external interfaces of the node, like the P2P port, which is sort of the most interesting surface security wise that we care about, or the RPCs, or whatever interface the node has available we can sort of use to test it. And Yeah, I guess, I don't know. What should we talk about next year? Do you want to do a demo maybe? Maybe that's the easiest way to get it running. So you get your terminal up, what do you have running here? Yeah. So the way it currently works, if you want to use this, there's a bunch of Docker files in the Fuzzer Moto repository, and they essentially set up the whole environment that you need to use the tool. What you see here right now is that I am in one of these containers that I've pre-built, so we don't have to wait for the build to finish here. In this container, we have a Bitcoin D, which is a custom branch that I made to reintroduce some bugs that we previously had. And then we We also have the FuzzerModo project itself, which comes with this FuzzerModo libafl tool, which is the fuzzer. And there are a couple of steps that are not that interesting to walk through here. That you have to like, there's a couple of commands you have to run to like, create the setup, for example, to like create this directory here. And maybe we can link to the documentation where all of those steps are described, but it's really just very manual, like execute this and then that, and then you have it. And yeah, so basically once we execute this command, it will start running the tool and we'll start sort of testing the node in various random ways. And hopefully eventually find some of the bugs that I reintroduced for this demo. So if we just start this, it takes a little bit at the start because it sets up and it creates a virtual machine and it sets up the Bitcoin D-nodes and then eventually it starts running here. And yeah, This is basically just some basic output. We can see how many total test executions we've done, how much coverage we've achieved so far, how fast we're going. So currently, we're doing 900, 800 executions per second, which is basically like 900, 800 test cases that we do per second. And then maybe the most interesting is the one at the end, the number of bugs we found. And so far we have not found anything. I am not sure how long, it might take like a couple minutes for it to find the first bug. But while that is running, we can go and look at some of the test cases that it's generating. I don't know, like sometimes it's, some of the test cases are not gonna be like super involved or interesting, but which directory did I use? Yeah. So. Here's a Silly question. How many Bitcoin core nodes do you have up and running at a gantt? Does it spawn maybe 30 of them or something? The way it works that there's one VM for each, well, you can specify on the fuzzer like how many VMs it should have in parallel. And then currently in this setup that we have here, there's one Bitcoin Core node in each VM. So we have like 32 because the machine has 32. Or is. 32 cores, exactly, we have 32 VMs. And in each of them, we're sort of testing one Bitcoin Core node. Yeah, and this folder here, the output folder has like for each instance that we're running, we have, so instance zero, for example, we have a queue, oops, a queue folder, which is the corpus. Actually, let me do this. So there's just a bunch of files in here that sort of describe an individual test case that we generated. And then we can run this input locally in this Docker container without, I just picked a random one. I don't know if that's going to be interesting, but we'll see. We can turn on some extra logs as well. Then we can run this input with the actual Bitcoin D binary. Then once we run this, we will see output from the test and also the Bitcoin D logs while it's executing this test case. It's just, that's a bunch of stuff. Yeah, this test case isn't like, we see there's like the Bitcoin core node survived. There's nothing wrong as far as we know. At least it didn't crash. And then if we go up, we can see here there's a bunch of logs of like, orphans being added and removed. Essentially just the test case seems to be submitting a bunch of transactions to the node. A bunch of ping pongs. Yeah, this is like where the test case essentially starts running. And we could do this for like all the test cases that we have in this queue folder, and each of them will be slightly different, exploring some slightly different scenario. Yeah, still no bugs. If we don't end up finding them soon, then I have also prepared, I ran this earlier and I have some of the inputs that actually trigger the bug so we can see what happens there too. It should find them within five minutes. Cool, I have one quick question about it. So you've got the coverage number, which is up to 9% now. So we're tracking upwards. I'm assuming as coverage increases, our chance of finding the bug goes up. What's the stability number over there on the far right? It says like 96%. Yeah, the stability metric essentially describes how deterministic the test is. So one thing that we want with fuzzing is that if you give the test the same input, we want it to behave the same. Like we want it to hit the same coverage. But software is like usually, or often software will not be deterministic. And this metric sort of tells you, is it deterministic or not? And if it's not 100%, then it's not deterministic. So the way the metric is calculated for so the way that coverage works is that the compiler instruments each control flow edge in your program. And then for each edge, you essentially have a bit in your coverage map. Then the stability metric is for all edges that you've seen in total, sorry, it's the fraction of the edges that are stable over the number of edges that you've seen in total. So I guess 95 percent of our edges are currently stable, and the other edges we've seen to be like randomly be hit. But yeah, it's, for me, yeah, it's not a super useful method really. I think if it goes like down significantly, then you should probably work on like making your first test more deterministic because yeah, non-determinism can prevent you from finding bugs. So you do want like all these tools are essentially designed with the assumption that your test is going to be deterministic. So if they're not, you degrade the efficiency of your testing effort. Wait, so hang on. Just so I understood the last bit, you design them so that they are the same every time? Yeah, exactly. Like the, oh, sorry, now we found one crash, apparently. Two, two now, maybe. It's usually, it'll find the same one over and over again. So the it doesn't be duplicate Again the one of the assumptions that fuzzing tools are Built around is that the thing that you're fuzzing is the germanistic Right got it. Okay, because you don't want to have to run if you run the thing multiple times You don't want it to be like slightly different or whatever. Okay, if you do coverage guided fuzzing then if you find something interesting you save it to your corpus and then if you pick that again and you mutate it, you're kind of making the assumption that you mutate it slightly to find something new. But then if you execute it again and all of a sudden something random happens and it doesn't even hit the code that you previously hit to save it into the corpus, now it's like something completely different. So it adds noise to your corpus if it's not deterministic and you end up doing more work on stuff that maybe isn't interesting. That makes sense. Cool. Do we want to go ahead and look at what these bugs are just as a, I don't know. Yeah, that should be quick. So go over to the other one. We can just see which instance. So we can see CPU 17 found all of the three. Then we can use the command I had here earlier. 17, I'll pick one of them. Oops. Crash, crash, crash. And now we should see at the end, crash totter not alive. Okay, so this crash looks like It is not deterministic because it didn't. Okay. I actually have not seen this. We might have to cut this because I don't know what this is. I'm guessing it is one of the bugs I introduced, but it's actually not the one that I was looking for. That is. Yeah, it's okay. I don't know. It's probably not an actual issue, but Yeah, this is not the one I was looking for, so we'll just pick another one. This is the same one. OK, they're all the same. Crash. Yeah, it's not a crash because I think this is like the node detecting some error that we can't recover from and then it shuts down. The actual one I was looking for is like an assert failure. Oh, got it, okay. I'm still guessing that this is caused by the patch I reintroduced. So let's see if there's, oh yeah, I stopped the fuzzer. So I can use, damn it. I do have the ones prepared that I was looking for. Okay, yeah, so this would be like an example of what the crash would look like if, what do you call it? Exactly, like this would be, when the fuzzer finds a bug, I normally reproduce the bug it found in this way to see all the output and potentially already see what the actual problem is, but sometimes you have to do more debugging afterwards to obviously figure out exactly what the problem was. So this bug, oops. This is an old bug. I think this was fixed in like 2013. And it was a divide by zero in the Bloom filter code. Okay. So this is The FBE signal is, yeah, I think a signal you get if there's like a problem with the arithmetic. So like a divide by zero, for example, we'll throw the FBE signal. And then because I compiled with the address sanitizer, we get this nice stack trace here, which at the top we can see there's the bloom filter hash and there's some like divide by zero in there that I reintroduced. And it found this because it sent into like it randomly like the fuzzers, some of the inputs tests that it was doing triggered it such that it tried to divide by zero. And so rather than have to come up with all the manual test cases as to what to ask, you just use the fuzzer to like hit basically the corner case where the zero is. So. Yeah. I think in like this specific bug requires like a sequence of one filter load message and then a filter ad, which adds nothing, which just adds like an empty byte array to the filter. And that's like the size of that empty array is what's causing the problem and the divide by zero. Got it. So this is not like a complicated bug. It was multi, It required multiple steps to trigger, right? And like if you, so like the difference between like using a fuzzer versus like, you would have to manually realize that you need to call these two commands in this way to cause it to crash, right? But the fuzzer can just try a bunch of stuff and find things without you having to figure out what to test, right? Maybe you could... Yeah. Yeah. Normally in unit tests or integration tests, you'll sort of codify what you expect your program to do correctly, but you obviously are not going to cover all the edge cases. And a fuzzer has a good way of removing your own bias for coming up with the test cases. So it'll try completely ridiculous stuff that you would probably assume to be fine or haven't thought about or whatever. And then it'll find edge cases like this. I don't know if this vibe was found with fuzzing back in the day, but it can be easily found with fuzzing nowadays. That's cool. Yeah, makes sense. Cool. Well, I think that was, for me, this is like a great example of how Fuzzimoto works, that kind of thing. You're gonna be in Brazil in two weeks to talk about Fuzzimoto at Bitcoin++. Is there anywhere else people can look to find your work? Like Fuzzimoto is up on GitHub. Is that a good place to look it out, try out the project, that kind of thing? People want to learn more? So there's the GitHub repo. It has a bunch of documentation, also a little bit on the inner workings on how it works, but obviously the code would be the best source to figure out how it works. There's also a introductionary blog post on the Brink blog, which also covers some of the design and architecture. Perfect. Oh yeah, I saw that. That was an amazing... You put that out just last month in January, right? And it'll be like a whole series. I'm not there's no fixed schedule for like the posts to come out But yeah, there will be more posts first of chapter one. Okay, cool Well, thank you for your time Nicholas. I really appreciate it and I'm looking forward to seeing what you've got for us in Brazil in a few weeks. Yeah, I don't know if there's anything else you want to leave a note or promote or whatever at the end for people to hear more about. Yeah, not really. Come to Brazil and you'll learn more about fuzzing from me and a bunch of other people as well. Yeah, it's going to be great. Cool. All right. Thanks Niklas. All right. Thank you. 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It's good. We're in Istanbul today. I think it looks like Istanbul. I'm not sure. It looks like it. I know people in the camera can't see but we are sitting in front of what I like to think is the nicest view in Istanbul maybe. Yeah. Not bad. Is this your first time in Istanbul? No, I mean been here several times. Been here a few times, that's cool. We're here for Bitcoin++ and we were just talking about how you're here giving a research update on a project you've been working on for how long now? I guess it's, I mean, officially since October last year, I would say. So it's like it's been a year and a half, I guess. Okay. Yeah, so it's kind of that. So about a year. Yeah. What was the, what's the project that you're working on? Yeah. So what's what's going on on our side is basically we're trying to figure out the way to define confidence and to verify the keys on Bitcoin without any software or without any changes. Yeah. No software. We're not getting it. Relax. It's like our arguing about the software is pointless. So we're trying to figure out the way, and we call this way Bitcoin pipes. Pipes. Yeah, effectively. And like it's, again, like it's an attempt to apply like a Fustopia level cryptography to induce conditional decryption of a key or of a signature to indicate to indicate the correct verification or the correct execution of certain computation off-chain from Bitcoin, non-interactively. Okay, so you're moving the computation off-chain. Yes. What is, so right now, computation is kind of on-chain when you run a script, right? And every node that gets a transaction that has a script in it executes the script. Using Bitcoin pipes, you're going to try and add more opcodes, is my understanding. So expand the range of what's possible to compute using a Bitcoin script, but you're going to make the computation happen not on everyone's computers. Where is the computation happening then? So basically, the computation can happen on anybody who's willing to prove that certain computation was done. So like it's probably going to be like on the user side or like on the specialized whatever like dedicated hardware a user can outsource the computation to or something. So I mean, yes, that's what it is basically. Is this client-side validation? Is this in the realm of client-side validation? No. Client-side validation mostly is about attesting that certain state happened on the user side. So after that you're submitting some merkle roots or something like hashes so a person can verify that and that they're working with the correct data and things like this. In here it's more about, and like also sure, it requires like everybody to have a consensus around the software you're validating the data with, so it's kind of implicit consensus you're having. And again, it's kind of the controller or the representer again decides everything, the fate of everything. So that's a little bit of a nuance. In here, we're not talking about like a client-side validation, we're talking about more like an attempt to... Okay, well, there is no specific requirement for this to be done on the client side or something. Probably will be done on a wallet side or a front-end application side or something. Bitcoin pipes also do not imply, do not require this implicit consensus of software which downloads the data and renders the state or something else. And it also doesn't require any interaction between who attests the correctness of a computation. It's kind of supposed to be non-interactive. So it's pretty far from client-side validation in terms of what does it get you and what does it imply. That's cool. So you've been working on this for almost a year now and you just gave a research update which I'm really excited to go watch the recording for when we get back to Texas. But what can you give us maybe like a short version of like what the update is, if that makes sense. Okay. So, like the initial idea, the initial kind of whatever construction and the endgame construction, I would say, of pipes themselves is that you can define a circuit, you can, you know, kind of encrypt some key, collectively probably, but with some MPC or something. You can give the ciphertext to a user or to an application, and you can make the user or like an application to perform some computation. For example, concatenation, or multiplication, or something else, you know, some missing opcode computation, or a missing piece of opcode computation. And then, basically, get a user or a frontend application to compute either a signature of a certain transaction which is supposed to continue with the execution of a certain application or to decrypt a key which will attest the successful application of this particular ZDP thing. Because this happens entirely on the application, on the user side or something else, it doesn't require anybody to talk with each other. It's kind of a non-interactive process. So that's the end game, how it should work. The current research update is like this kind of construction, non-interactivity, requires to have a functional primitive, which is kind of a post-opia level primitive, like functional encryption or witness encryption, which is still pretty, you know, kind of still an open problem. And sure, there are a lot of like special purpose witness encryption schemes, there are a lot of like special purpose functional encryption schemes, but like none of them fit this purpose. So the research update was primarily about how do we go after this functional encryption slash web encryption scheme, which would fit the purpose. And it's kind of a little bit of a dive into, it's kind of a little bit of a dive into the life of people who do obscure cryptography. Okay. So your research work consists of reading the literature, talking to people, or are you actually like building like toy protocols or primitives? Okay. Toy protocols, building, trying to understand what security properties they induce, which performance properties they induce, which properties from the user experience perspective they induce. For example, there was a prototype protocol on our side, which it's still an option. That's what we effectively called Pipe-C1, is when we tried to induce the conditional decryption, like witness encryption from QFE, from quadratic functional encryption, and then we're like, oh, it might be not really secure, but can we make it secure enough? And there was this whole idea that, it still kind of is, there was this whole idea that we could probably just, even the smallest gap between the honest evaluation of the scheme and the malicious evaluation of the scheme, we could amplify it with the size of a witness, like to the point where the malicious execution of the scheme becomes impractical. But like what is the evaluation is still practical. Got it. That's interesting. Yeah. So this kind of stuff. Like here we play with assumptions, we play with what the user needs. Like what's the cost people are ready to eat? And like what's the- So are there any costs for clients? Like, so I know like for DLCs, are you familiar with DLCs? Absolutely. Okay, yeah. So one of the things is like the setup cost is quite high, right? They have to accept, there's like a certain amount of time it takes to compute all of the signatures that you have to sign or whatever, and then there's a space requirement of what you have to save in order to have a DLC contract. What are the costs, I guess, of using these pipe scripts? Okay. Is it a script or is that the right word? Just pipe. Let's call it just pipes. Just pipes, okay. Like pipe script is a separate thing. We'll come to that. Okay. Maybe next year, I guess, but whatever. So pipes effectively induce costs, specifically pipes you want, induce quite large costs in terms of what it gets to decrypt the key or decrypt the signature. Again, basically because that's the assumption of the scheme itself, when you're inducing the security from this gap. So this kind of stuff. Basically, this computational complexity is why such a witness-encryption scheme is possible. At least theoretically it's possible. So that's what it is. In terms of like, can we make it cheaper? Can we make it more interesting? Can we make it like, like, it's beautiful on the client side, on the phone, on like laptop, you know? That's effectively why we started working on what we call pipes v2. Okay. Which is supposed to be a little bit less obscure. It's supposed to have more classic security definition with like hey the attack cost should be exponential ideally and like the execution should be as cheap as possible. Got it. It's kind of like a push towards two directions to make it more compliant with traditional, with what people traditionally assume when they talk about the product. Got it, okay. And sorry if I missed it, but If a client is trying to use a pipe, are they going to have a CPU cost to do the decryption? Yes. It's basically a CPU cost. Got it. We do not expect people to use it for a single opcode or something. You can for sure. You can do that, absolutely. But it's just a little bit too expensive. So we expect people in the majority of use cases to be induced from the usage, for example, of ZK roll-ups. This is how true ZK roll-ups become possible. You basically can do the state transition verification within the ZTP, a single transaction, a semestic state transition verification. No optimistic games, no whatever. Right. Yeah. No interactivity or something. Shut the transaction into the mempool, it's verified. That's it. You can't undo that. That's cool. That's what it is. So it would solve all this security trade-off assumptions that they're having to make with the BitVM construction, right? Basically. Basically. That's cool. OK. At the cost of making the client have to do a lot of computation? Yes. Yes. The CPU cost is the downside of this. But again, we're working on the V2. Yeah, OK. Can you quantify what level the cost is? Is it something that someone with a phone could do, or is it like, you need like a GPU, does it have like a dollar value? You'd need a bunch of commercially available servers. Interesting, okay, so that is quite high. But you were saying it's not like client-side validation where each client is responsible for doing the validation themselves. This is like, you can almost like farm it out to someone else to do the verification for you. And once someone's done the verification, is it available, then it becomes widely available for everyone to use, if that makes sense. Once somebody's done the verification, the key is basically decrypted, the key becomes available. So like this key, whatever the transaction is being done with this key or like with the signature can be effectively an attestation of the fact that the successful ZKB verification has happened. So basically anybody can sign it or anybody can do anything. And it's not harmful to even write this private key on the wall. Right. And sure, please do the transaction for me. I don't want to pay the fees. Right, got it. Yeah, but basically you need someone to invest in doing the work to decrypt the private key. A little bit, yes. Yeah, but once that happens, the keys can be made widely available. It's not like a thing. Okay, cool. And anyone of course can invest in decrypting it. Got it, that's cool. Do you have like a, yeah, that is a question. So assuming you had access to like, I don't know, these servers, do you have any estimate of like what a cost would be for it? Abdel had a talk earlier where he was like, it was like $13 to sync the chain using ZK stuff. Do you have a similar number that you've computed? Yeah, we've had some estimations of this for the witness encryption induced from PUC. Again, this is like security assumptions of that, again, disclaimer, are not the best ones. We're like, we're working on fixing them. But there was like an estimation of that. In the end of the day, we estimated effectively how much of Bitcoin can you store behind a single pipe, like behind a single pipe of a version 1. Okay. And we resulted in like that you can store maybe like, I don't know, one hundredth of a Bitcoin, like one percent, like whatever. So it would be, I think, a hundred thousand SATs. Basically. Yeah. Basically, like at most. With the current prices. You said 1 one hundredth or... One hundredth. One hundredth? One divided by a hundred. I think that's one million sats. Because there's a hundred million Satoshis in a Bitcoin. So like basically the assumption was made, Basically the assumption for that estimation was made from the fact that you've got to make it impractical for the attacker to try to even mess with this. And we've got to make it just cheaper to mine Bitcoin than this. Because I mean, again, imagine somebody tried to attack this. Will they succeed? Sure, they will. We know they will because their attack complexity for v1 was supposed to be polynomial. We know that they will succeed. Sure. What they will get? They will get something which is worth less, like thousand times, than they've spent on computing this. Got it. So like, what's the point? Right. And sure, maybe you can do that just for the sake of messing with the protocol. Absolutely. It's economic security, so to speak. Basically, that was supposed to be the thing for v1. For v2, it's going to be proper. So economic security is basically, it's more expensive to do the computation than the amount of value you can expect if the computation is successful. What is proper security? If economic security is not proper, what is proper? Just that you're not even able to do the calculation? Yeah, like proper security is exponential attack cost. You will not have enough of compute in the universe to like... To do it, which is similar to Bitcoin private keys, right? Yeah. So it's going to be basically the same. Cool. That's very cool. So you just gave a research update on what's going on. What's new? What's next? So you're continuing work. Like you kind of mentioned that maybe there would be a script for it at some point in the future, but not currently. Yeah, there is like, since pipes effectively induce, since pipes effectively can induce the extension of script with like necessary opcodes. This kind of extends the script itself. And this gets you to what you can call, like, you know, we had mini script, we had script, we had tab script, and you have pipe script. Pipe script. Like an extended set of opcodes you can use or like. C++ almost, I'm sorry. Kind of, kind of, kind of, kind of, kind of, kind of, kind of that. For those of you who aren't aware what the difference is, C++ is supposed to be like an extended set of C, right? Like, yeah. So it's kind of like that, like pipe script. So when you have jumps, when you have like where you have... Script++, sorry. Yeah, Script++. Like, well, where you have jumps, where you have like multiplications, where you have like count or anything else you want and it's not harmful. Got it. Yeah. Cool. I'm trying to think if there's any, so if people are interested in learning more or maybe are you looking for contributors? Like, is there, is there ways people get involved in it or learn more about your research and what you're working on? Where would you send people, I guess? Well, I mean, at this point, it's just we're publishing stuff for the website and like then it's just sitting there. So I mean, that's kind of that. Okay. We have a little chat like set up for like public involvement. But again, trying to be We're trying to be careful because it's easy to hype people up for witness encryption. But when you're like, you know, you got to actually do the thing before you hype people up. You got to provide people with like the actual security. You said there's a chat. Is that on Discord? Is that on Telegram? Just Telegram. It's on Telegram. Yeah, I was talking to Robin earlier and he was joking that everyone thinks on Telegram these days. Yeah. It sounds like you guys are no exception to that. Cool. I'll see if I can find the link and put it in the show notes, so people who are interested. And then for witness encryption, that's a new term that I'm not familiar with. I'm sure many Bitcoiners probably aren't very familiar with it either. Is there a place that people can learn more about it? Or what's the best way to get into the witness encryption rabbit hole if someone's interested in learning more about that? Honestly speaking, it all starts with GARC and Dan Bonet papers. Okay, all right. Is that? Dan Bonet papers. Who is GARC? Is GARC a protocol? No, GARC is one of the inventors. One of the inventors. Okay. It sounds a lot like, you know, you could like see how that's like a GARC thing. Or like Frank Waters and this kind of people. No way. They did a lot of good, they did a lot of good paper on that. They did a lot of good papers on that. Cool. So. He didn't name something after himself? GARC? No. No, they did not. They did not. I mean, Rachel Lynn or like recently, recently I saw people popping up here and there with like doing interviews with Rachel Lynn about I.O. And things. She's also one of the godfathers of this. Okay, cool. Maybe we can get her to the next conference or event. So you're here in Istanbul this week. Are you going to go to any other events while you're here? What's next on your conference schedule? Is there somewhere people can see you talk next? Honestly speaking, it's the primary thing I came by here. I mean, basically because that's the primary thing we're occupied with. Like this, though. Just give people a sense about what's going on. Because it's been some time. Yeah, definitely. Cool. Well, we're really glad you're here and hope to see you at another event sometime soon or hear an update on Pipes or maybe a launch announcement. Yeah. Oh, what did you call it? A splash. Yeah, a splash. We got a splash to make. So cool. Thank you, Misha. Yeah, all right. 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Filmed last year in Istanbul at Bitcoin++ Scaling Edition.\n\nSign up for one of our upcoming dev conf at https://btcpp.dev\n\nWebsite: https://btcpp.dev/\nX: https://x.com/btcplusplus\nNOSTR: https://iris.to/npub1dwah6u025f2yy9dgwlsndntlfy85vf0t2eze5rdg2mxg99k4mucqxz7c52\n\n#btcplusplus #devconf #bitcoineducation #bitcoinconf #bitcoindev #bitcoinconference #bitcoin #cypherpunks", + "date": "2026-03-20", + "youtube": { + "description": "We talked to Misha Komarov about Bitcoin PIPEs, which enables covenants and ZKP without a soft fork via off-chain computation. Filmed last year in Istanbul at Bitcoin++ Scaling Edition.\n\nSign up for one of our upcoming dev conf at https://btcpp.dev\n\nWebsite: https://btcpp.dev/\nX: https://x.com/btcplusplus\nNOSTR: https://iris.to/npub1dwah6u025f2yy9dgwlsndntlfy85vf0t2eze5rdg2mxg99k4mucqxz7c52\n\n#btcplusplus #devconf #bitcoineducation #bitcoinconf #bitcoindev #bitcoinconference #bitcoin #cypherpunks", + "tags": [ + "btcplusplus", + "devconf", + "bitcoineducation", + "bitcoinconf", + "bitcoindev", + "bitcoinconference", + "bitcoin", + "cypherpunks", + "niftynei" + ], + "categories": [ + "Science & Technology" + ] + }, + "deepgram_output": "deepgram_2026-06-26T074613Z.json" +} \ No newline at end of file