Coming to DSS 2026: @0xA5DF “Auditing Is Not Bug Hunting: Securing Systems Through Risk Management” Add this talk to My agenda: defisecuritysummit.org/2026/… Tickets: luma.com/9qtxqqxx

The Avalanche Audit Marketplace is live on the Builder Hub 🔺 One request reaches all Ava Labs vetted firms. Quotes stay private, you pick one, and the program can cover up to 75% of the cost. $0 fees for builders and auditors. Request quotes 👇

I’ll be in Bulgaria this week for @ETHSofiaBG 🇧🇬 Looking forward to meeting builders, researchers, and institutions and talking about what security and software correctness look like as AI changes how we build software.

The Book of Ethereum (@Bookof_Eth) published this chart, and it honestly blew me away. 291 projects, protocols and communities. An ecosystem spanning finance, payments, lending, identity, tokenized assets and much more. Independent teams building businesses on shared infrastructure. Each new application can connect with what already exists. If you invest in the Magnificent Seven, take a closer look. Here is where I see potential connections: • $NVDA - AI agents buying compute, paying for services and transacting around the clock. • $MSFT - Enterprise agents connecting business workflows with contracts, payments and settlement. • $GOOGL - Cloud infrastructure and agent commerce. Google Cloud already offers Ethereum nodes. • $AMZN - Global commerce, merchant payments and cloud infrastructure. AWS already supports Ethereum. • $AAPL - Wallets, payments and digital identity bringing onchain services into everyday life. • $META - Messaging, creator payments and commerce connecting people across borders. • $TSLA - Autonomous fleets and robots that could eventually pay for energy, data and services themselves. Ethereum and its L2s could provide shared financial infrastructure across parts of that economy. I keep thinking about @elonmusk asking Vitalik back in April 2019: “What should be developed on Ethereum?” Thinking a decade ahead? Wouldn’t be the first time. At the foundation sits $ETH paying transaction fees, serving as collateral and helping secure the network through staking. Ethereum’s explanation. Institutions understand infrastructure. As more of their business depends on Ethereum, owning and staking $ETH could become a strategic priority. And finally, governments. Tokenized sovereign debt. Public payments. Financial infrastructure. If those activities increasingly rely on Ethereum, participating in the network’s security could become a matter of national economic strategy. This is the institutional thesis I believe will win: ETH becoming a strategic commodity for an expanding onchain economy. I don’t think the market has priced this in. Most portfolios still own ZERO $ETH I think new ATHs are closer than many imagine. And the FOMO into $BMNR and $SBET could be massive. Do your DD. Ask your financial advisor why this hasn’t been part of the conversation. It’s your money.

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.

Seems like crypto is going mainstream, I'm checking it in Barcelona this week. Come find me at @EBlockchainCon to talk about AI security, formal verification, and more.