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Inside Aztec

Inside
Aztec

purple_2
Aztec Network
7 Aug
xx min read

Alpha V5 Proving System Vulnerability

Contributors identified a critical vulnerability in Aztec's V5 Alpha proving system, the kind of finding Alpha testing exists to surface, with the fix planned for V6.

Status

Core contributors identified a critical vulnerability affecting the V5 Alpha proving system on 27 July 2026 through internal AI-assisted auditing.

V5 remains Alpha software. Critical findings can arise during this phase, and the audit process exists to identify them before broader deployment. This finding places V5 funds, applications, and contract state at risk.

Treat funds and applications on V5 as exposed to a protocol-level failure until contributors complete incident response work and operators carry out the required network actions.

What we are disclosing

An attacker may be able to exploit a flaw in the current V5 proving system by constructing a proof that passes verification for a transaction the network should reject. If accepted, that transaction could produce a state transition outside the rules V5 intends to enforce.

Contributors cannot determine whether anyone exploited the flaw before this finding. The affected system lacks the information needed to distinguish ordinary accepted transactions from transactions accepted through the flawed proving path. Historical chain activity cannot establish whether exploitation occurred or quantify its impact.

Application safeguards

We expect application teams to prepare safeguards in the coming weeks.

Those safeguards may include changes to application controls, deployment procedures, user flows, and migration plans. We expect each team to assess its contracts and determine which protections fit its architecture and users.

We expect teams planning a V5 deployment to pause that work until contributors publish further guidance. We expect teams with live contracts to review their ability to limit user exposure, isolate affected functionality, and move users to fresh deployments if needed.

We expect applications that maintain administrative or emergency controls to assess whether those controls can reduce user risk during the incident timeframe.

Next steps

Core contributors are working with operators, application teams, and bridge operators as applications add security guards around affected flows.

The findings from this incident will inform the V6 release, including circuit updates that prevent the network from accepting proofs tied to an affected proving system.

V5 launched as Alpha software, with V6 planned for later in 2026. Contributors will publish a security roadmap covering the remaining work and release path.

Known vulnerability status

Reviewers have not identified other high-severity or critical V5 Alpha vulnerabilities at this time.

Internal and external human audits have completed, and contributors continue AI-assisted auditing. Alpha is the period for identifying faults before production deployment.

Most Recent
Community
4 Aug
xx min read

Dark Forest Aztec Game Goes Live

Dark Forest is a real-time strategy game played across a procedurally generated universe where most of the map is hidden. You cannot see rival players, their planets, or their fleets. You only know what you have explored. Everyone shares one universe, and nobody has the full picture.

In most onchain games, every position and every move is public, because the chain is public. Dark Forest used zero-knowledge proofs to break that assumption: players prove their moves are valid without revealing where those moves came from. The result is a game of hidden information running on a public network.

Dark Forest Aztec ports the original Dark Forest 0.6 to Aztec. It keeps the gameplay from the original and rebuilds the privacy layer on Aztec's programmable privacy.

A note before diving in: this is early, experimental software on Aztec Alpha V5. Treat it as an alpha and play accordingly.

The universe you cannot see

You start on a single home planet with almost the entire map dark. To find anything you mine the universe, running a client that explores coordinates and reveals what sits there: unclaimed planets, resources, and eventually the edges of other players' territory.

You are never handed a view of the board. You earn it one region at a time, and everyone else works under the same fog.

What is hidden on Aztec

Your home coordinates and your fleet movements are private state, expressed as first-class private notes on Aztec. Your location and where you send energy stay hidden, enforced in the contracts by zero-knowledge cryptography.

What sits onchain is a set of cryptographic commitments. Instead of storing every planet's full details in the open, the contracts store Poseidon2 hashes of entity state. When you make a move, your client supplies the full state, the contract checks it against the stored hash, applies the change under zero-knowledge constraints, and writes a new hash back. Full game state lives offchain and gets rebuilt from public logs by an indexer, which is what renders your map without exposing every player's position.

So you can prove you made a legal move from a planet you own without revealing where that planet is. Aztec applies the same principle to private payments and private contracts.

How you play

Four actions carry the game.

Explore. Your explorer sits in the bottom left. Set it running and it uncovers the map around you, surfacing planets, resources, and other players.

Send energy. Most planets produce energy. Click and drag from a planet you own toward a target to capture or weaken it.

Route silver. Asteroid fields produce silver. Move it to your planets and spend it on upgrades, or send it to a Spacetime Rip to convert it into score.

Hunt artifacts. Some planets hold artifacts. Your Gear ship discovers them. Once harvested, you deposit them on planets to boost stats.

Four stats drive most decisions.

Energy is the core resource. Planets generate it over time up to a capacity, and you spend it on everything: claiming planets, reinforcing your own, attacking rivals. Two details matter. Moves are taxed, so a flat percentage of a planet's total capacity burns every time you send energy, which discourages small frequent moves. And energy decays over distance, so send it too far and almost nothing arrives. A common rule of thumb is to let a planet fill to about 75%, then send it down to about 25%.

Defense reduces the damage incoming energy does when it lands. Higher-level planets often have lower defense, but they hold much more energy, so they still take more to capture. Defense matters most on front lines.

Range sets how far a planet can send energy. It governs how fast you expand and how efficiently you move energy inside your own empire, since shorter relative distances mean less decay. Good range also lets you strike deep into an opponent's territory.

Speed sets how quickly a move arrives. Usually secondary, though a fast strike can land before a rival reacts, and some playstyles reward capturing many nearby planets quickly.

Planets can also be upgraded with silver and enhanced with artifacts. Space types carry different multipliers, from mild Nebula to punishing Dead Space, so where a planet sits changes how it plays.

How scoring works

There is a scoreboard, and territory alone does not win it. This round scores two activities: discovering artifacts with your Gear ship, and withdrawing silver through Spacetime Rips.

Point values from the in-game help page:

  • Each unit of silver withdrawn: 1
  • Common artifact: 2,000
  • Rare: 10,000
  • Epic: 200,000
  • Legendary: 3,000,000
  • Mythic: 20,000,000

Silver accrues one point at a time. A single Mythic artifact is worth twenty million of them, so artifact hunting decides rounds and silver withdrawal sets your floor.

Silver has two competing uses. Spend it on upgrades and your planets get stronger, extending range and hardening defense. Withdraw it through a Spacetime Rip and it becomes scored points, but it is gone. Every unit is a choice between building the empire and banking points.

Upgrades tend to win early, since a stronger empire reaches more asteroid fields and finds more artifacts. Late in a round that calculation flips, because a planet you never use is worth less than points already scored.

Artifacts do both jobs at once. They score on discovery, and once deposited they boost a planet's stats, which makes the next expedition easier.

Why you explore

Nothing happens until you find something to act on. Your explorer turns dark space into planets you can capture, asteroid fields you can mine, and artifact-bearing planets you can raid. Sitting still means no new energy, no silver, no score.

Exploring also buys information. The map you have uncovered is an advantage nobody else holds. Knowing where high-level planets sit, which asteroid fields are unclaimed, and where space types shift lets you plan further ahead than someone still working through their starting region.

You find other players as a byproduct. There is no player list. You explore outward until your revealed region touches territory someone already owns: a planet in another player's colors, sitting where you were about to expand. Their home coordinates stay private, so you learn something narrow. Someone is here, roughly this direction, holding this much. You infer the rest, and you have no way of knowing whether they found you first.

What happens when you run into someone

You have three broad options.

Stay quiet and keep growing. Nothing forces you to engage. Keep exploring elsewhere, keep routing silver, keep upgrading. Your positions stay private, so silence costs you only time, which is what you want if they are stronger. The risk is that they are doing the same thing faster.

Fortify the border. If the contact sits somewhere you cannot lose, spend energy hardening the planets facing them. Defense is worth most where an attack will actually land. This keeps the option to fight without committing to one.

Attack. Send enough energy to overwhelm the target's defense and the planet becomes yours, along with its production and its position as a staging post. Higher-level planets are the prize and take proportionally more to crack.

Attacking costs more than energy. A move that lands tells your rival where you strike from, and that you are close enough to be worth answering. Retaliation can then come from directions you have not explored, launched from planets you cannot see.

Multiplayer in practice

Everyone plays one shared universe in real time. No turns, no lobbies. Energy regenerates whether you are watching or not, moves stay in flight while you sleep, and rivals expand while you are away from the screen.

Most strategy games let you watch a threat approach. Here you tend to see the consequences: a planet you owned this morning in someone else's colors, an incoming move you notice once it is already close.

That produces a particular kind of paranoia. You are trying to find everyone else while avoiding being found, and every expansion is a strategic bet that the space ahead is empty.

Information becomes tradeable, because it is scarce. Players compare notes, warn each other about aggressive neighbors, and agree who expands where, then break those agreements when the scoreboard makes it worth breaking.

Why it matters beyond the game

A fully onchain game where players cannot see each other's positions is hard to build, and building it well says something about the platform underneath.

Hidden state, private notes, and client-side proving are the same building blocks behind private applications across Aztec. Dark Forest is a way to watch them work.

Getting started

Dark Forest Aztec is playable now as an alpha. Expect a learning curve; the original was famous for it. DFArchon maintains onboarding material and a community for new players. Round One is live. The universe is dark, and everyone else is out there somewhere. Go find them, quietly.

Play Now

Follow the Builders

DFArchon on X

Source and docs

Aztec Network
22 Jul
xx min read

How Gas Works on Aztec

Gas on Aztec

Gas on Aztec is known as Fee Juice and is used to pay for transaction costs. This is the same as $ETH on Ethereum. Some apps will handle transaction costs for you under the hood, but if you are using a browser extension wallet, you will not be able to send transactions without it. Fee Juice can be obtained by bridging the $AZTEC token on Ethereum to the Aztec Network L2. This means that under the hood, all activity that happens on Aztec is underpinned by the $AZTEC token bridged into the network. Some bridges like Shield (by human.tech) handle this for you, allowing you to allocate a portion of your bridged transaction to convert into Fee Juice and land in your wallet automatically.

Public vs Private Assets

Assets and transactions on the Aztec Network can be either public or private. If you bridge publicly, your tokens will arrive as public, traceable tokens visible to all. Privately bridging, on the other hand, will give you private assets that are visible only to you. These assets can then be sent privately to another user or wallet without ever revealing who you are, what tokens were sent, how many, or who the recipient is.

Public vs Private Gas

Like tokens on the Aztec Network, Fee Juice (gas) can also be public or private. The reason for this is that even if what you are sending is private, the gas you spend to execute that transaction could still be visible if you are using public Fee Juice, potentially revealing transaction patterns and activity. Private Fee Juice keeps your entire transaction footprint hidden. When you send a private transaction, you can use private Fee Juice, and when you send a public transaction, you can use public Fee Juice, which means your transaction costs are always aligned with the type of transaction you're making.

Fee Juice in Apps

Aztec has native fee abstraction, which means apps could let you pay for transactions in any token you want, or cover your fees entirely. Apps like Nyx may choose to cover part or all of a user's transaction costs, or allow you to pay in tokens that are convenient for you. This means you will most likely never see Fee Juice in an app; instead, you'll pay in whatever makes sense for what you're doing, on your terms. Similarly, you might never even see an Aztec wallet at all, because the app itself becomes your interface that you connect to using your MetaMask wallet.

Fee Juice in Browser Wallets

If you're using a browser extension like Azguard, you'll manage Fee Juice directly in your wallet alongside your private and public balances, converting between tokens as needed to cover transaction costs.

When you bridge tokens in, you'll need enough Fee Juice to cover the cost of your first transaction, then you'll need to monitor how much Fee Juice you have available to make transactions. Browser wallets will allow you to send either publicly or privately to other users and will default to using either public or private Fee Juice depending on the type of transaction. Both private Fee Juice and public Fee Juice will appear by default in your token list.

Wrapping up

How you handle Fee Juice depends on where you're transacting: apps can abstract it away entirely and let you pay in any token, while a browser wallet like Azguard puts it in your hands to manage across public and private balances. Match your gas to your transaction, keep private activity private down to the fee, and you move on your terms.

Aztec Network
21 Jul
xx min read

Introducing Alpha V5

The Aztec Network today activated Alpha V5, a major protocol upgrade passed by token-holder governance and executed onchain. Alpha V5 reduces private-transaction proving times by more than 2x compared to the previous version, lowers the cost of a fully private transaction by roughly 50%, resolves the critical issues found in V4, and sees the first wave of apps go live. Users can now send private transactions and earn yield on Aave simply by connecting their Ethereum wallets on Nyx, bridge from Ethereum to Aztec using Shield or TRAIN, privately collect NFTs on RavenHouse, or play Dark Forest Aztec, a hidden-information strategy game in a universe that lives entirely onchain. 

"Alpha V5 continues Aztec's work at the frontier of client-side proving, with cryptographic breakthroughs that cut proving times by more than half this release," said Zac Williamson, Co-founder, Aztec Foundation. "We believe Aztec is now the fastest system in the world for proving a fully private transaction entirely on a user's own device, and every release moves the industry closer to private transactions at public transaction speeds."

As the only decentralized privacy L2, Aztec is the credibly neutral privacy layer for Ethereum. Aztec allows anyone to write smart contracts that include both private and public aspects – every private transaction is proven on the user's own device, so no operator, sequencer, or intermediary can see the data. The Alpha V5 proving improvements come from cryptographic advances that make this client-side proving faster than any prior release. The network remains in alpha, but with V5 it is ready for teams to begin building and deploying applications.

Performance - 2.5 second fully private transactions 

Making private transactions practical comes down to how quickly a proof can be generated on a user's own device, without offloading that work to a server that would learn what the user is doing. On Alpha V5, proving a private token transfer natively now takes approximately 2.5 seconds on a consumer laptop, down from 5.2 seconds on V4, and about 6.8 seconds in a browser, down from 12.5 seconds. Across every measured transaction flow, client-side proving times improved by approximately 2x compared with V4.

Bench machine: an M2 MacBook (12 cores, throttled to 8). "Native" runs Aztec's C++ proving binary; "WASM" runs the same prover in a browser engine (Node on V8).

Alpha V5 lowers ECDSA signature-verification cost by approximately 2x, speeds up Poseidon2 hashing by approximately 3x, and reduces the protocol circuit gate count by approximately 50% (gate count is the number of individual operations a proving circuit must perform, and it is the main driver of how long a proof takes to generate). Each of these lowers the amount of work a device performs to prove a transaction, and the reduction in gate count in particular compounds across every proof the network generates.

Apps - send, receive, and earn privately on Ethereum

Alpha V5 launches the first wave of apps on a network where privacy is built into the protocol rather than managed by an operator. On other networks that claim privacy, transactions still pass through an operator or node that reads them in plaintext, or depend on a viewing key that a third party holds, so users rely on someone else to protect their data and to decide when it gets disclosed. On Aztec, every private transaction is proven on the user's own device, so the app, the sequencer, and any operator never need to see the underlying data. Nyx is one of these apps, allowing users to privately send transactions and privately earn yield on Aave. 

"On Ethereum, everything you do is public. That's why we built Nyx: a private account governed by your Ethereum wallet", said Nikhil, Co-founder of Nyx. "Now you can send, receive and earn in private. Nyx was the first app live on the Aztec Alpha, and we're excited to expand participation to more users with the added stability of Alpha V5."

Other apps on Alpha V5 include Azguard and Nethermind (wallets), Shield, TRAIN, and RavenHouse (bridges), and the Aztecscan block explorers. Also launching is Dark Forest Aztec, a game where users explore a universe, control planets, manage planetary energy, expand territory, and launch attacks through strategic play with private state and hidden actions.

Dark Forest Aztec private universe-building gameplay

Lower costs, higher security 

Transaction fees on Aztec come from two main sources: the cost of proving a transaction and the cost of verifying the rollup proof on Ethereum. Alpha V5 reduces both. It lowers the network's proving-cost parameter by 50%, and it reduces the L1 gas required to verify a rollup proof by approximately 40%. Because rollup proofs are verified on Ethereum and that cost is shared across all transactions in a batch, the L1 reduction lowers fees for every user, while the lower proving-cost parameter reduces the per-transaction proving fee directly. Together, these bring the average cost of a fully private token transfer to under a $0.05 transaction cost.

Alpha V5 also hardens the network on several fronts. It resolves critical vulnerabilities found in Alpha V4 along with additional bugs discovered since launch. Aztec's bug bounty program on Cantina also drew more than 234 security researchers to participate. The network remains in alpha, and further bugs may surface as usage grows, but each release has closed the issues found in the last and strengthened the protocol against new ones. With the critical V4 issues resolved and these safeguards in place, Alpha V5 is stable enough for teams to begin building and deploying applications.

Availability

Alpha V5 is live now, view the Alpha V5 landing page for a full list of features, performance updates, and live apps to explore. 

About Aztec

Aztec is the only decentralized, privacy-first Layer 2 on Ethereum. Developers write private and public logic in the same smart contract, and private functions are executed and proven on the user's own device, so no operator sees the underlying data. The protocol is upgraded through onchain governance, and the network settles to Ethereum. For more information, visit aztec.network.

Aztec Network
30 Jun
xx min read

Inside an Aztec Transaction

On Ethereum today, each transaction reveals everything publicly. The token you moved, the size, the timing, the wallet it came from, every action you take. Given the limitations of this type of transparent network, the industry is now focusing on bringing privacy onchain as a top priority. The response to this has mostly been to enable private transactions that shield transfers in various ways. But when we look at how privacy works on Web2, it’s clear that users and developers need granular privacy controls: the ability to decide what is public or private and who is able to see different types of data.

Aztec was built so that one transaction can carry two halves. A private half that runs on your own device and never leaves it, and a public half that the network runs in the open. Apps can choose which aspects are private or public, and users can choose what they want to reveal and when.

This article will follow an example transaction on Aztec: a vote in an onchain election built on Aztec, where who you are and which candidate you chose stay private, while the running tally for each candidate stays public for anyone to verify.

Public and private in one move

Picture the vote you cast in our example as two aspects that seamlessly weave together. In the first step, you act in private: an app records your vote on your device and hands the network a proof that the vote is valid without revealing it. In the second, the network acts in public: it checks that proof, then adds one to the chosen candidate's public tally. It is one transaction: one part stays with you, one part goes to the network. Both parts end up recorded onchain, in two separate state trees, one private and one public. The walkthrough below follows how these two aspects work together and what this means for how your transaction lands onchain. 

It starts on your device

You open the voting app and connect an Aztec wallet. That first step looks like any onchain app. The difference is inside the wallet. An Aztec wallet carries a private execution environment, the PXE, pronounced "pixie", which runs on your phone or in your browser. The PXE is where the private half of your transaction executes, and where the proof of that work gets made, on your hardware, under your exclusive control.

Every account on Aztec is a smart contract rather than a bare key. That design, account abstraction, allows a wallet to authorize a transaction however its owner chooses without writing an identity onto the network for everyone to read. The wallet is the front door, and on Aztec you can decide if the door is open or closed, who you share your information with. 

The private half runs on your device

The voting app is a smart contract with two kinds of functions. The private functions run first, and they run inside your PXE. Your identity and the candidate you picked are the private inputs, and they stay on your device.

The only thing to leave your device is a proof confirming the legitimacy of your vote. Aztec's client-side proving system, Chonk, takes the private execution and produces a zero-knowledge proof: a compact cryptographic receipt that your vote followed the rules, that you are eligible, and have not voted before, while revealing nothing about who you are or who you voted for. Think of it as a sealed ballot the network can confirm is valid without opening it. The network learns only that a legitimate vote happened. It does not learn how you voted, or even which account voted. 

This is the part that used to be too slow to be practical. Generating a proof on a phone was the bottleneck every privacy app hit. Aztec’s Chonk is purpose-built for fast proving on low-memory devices, both natively and in the browser, so the private half runs on the device in your hand instead of on someone else's server.

The public half runs in the open

Some elements of a vote should be public. The tally is shared infrastructure, the number everyone relies on to trust the result. Thanks to programmable privacy on Aztec, the app marks that part public. Public functions live on the network and run in the open, the way functions do on Ethereum.

On Aztec, private and public logic live in the same contract, and the developer decides which is which, function by function and variable by variable. Programmable privacy is a dimmer, not a switch. The voting app turns it up on the individual ballot and turns it down on the running tally. That boundary is a design decision written into the contract, and it is the thing no transparent chain and no fixed-privacy chain can offer.

The network checks the proof and runs the public part

Your vote leaves your device as a bundle: the zero-knowledge proof of the private half, plus the call to the public function that updates the count. It goes to Aztec's sequencers, a decentralized set of thousands of independent operators, with more than 3,500 of them running the network today.

The sequencers do two jobs at once. They verify the proof of your private vote, confirming it is valid and eligible without seeing the choice behind it, and they run the public function that adds one to the chosen candidate and updates the public tally. Your ballot stays sealed. The count goes up by one for everyone to see. The same proof guarantees you cannot vote twice, even though no one learns which ballot is yours.

Two state trees, both onchain

Aztec has two main state trees, and both live onchain. One holds private state, the other holds public state, so the full record of what happened sits on the network rather than on any one person's laptop. The two trees store each record in two different ways depending on if it needs to be private or public. 

The private tree uses a UTXO model, the same note-based design used by Zcash. In this model, state is written as commitments: each entry is a sealed record that a valid vote was cast, with the voter and the choice kept private. Just like with Zcash or Bitcoin, you do not edit a private entry in place. You write a new one, and the design stops the same vote from being cast twice (old state is nullified). The vote stays private, and the record of a legitimate vote happening is onchain for the network to check.

The public tree uses an account-based model, the same shape Ethereum uses: values that update in place, readable by anyone. This is where each candidate's tally lives.

One transaction wrote information to both trees. The private tree recorded that you voted, sealed. The public tree recorded the new totals, in the open. Everything is onchain. The difference between the two trees is how much each one reveals.

Every private app on Aztec writes into that same private tree. A vote, a payment, and a payroll run all land in one shared record of activity, so each user's privacy grows stronger as the network grows, instead of splitting into a separate pool for every app.

A block is proposed, and Ethereum records it

Aztec is an L2 on Ethereum, so everything settles to Ethereum L1. A sequencer on Aztec gathers transactions into a proposed block. Other sequencers validate it before it goes to Ethereum's pending chain. At that point the block sits on Ethereum, ordered and recorded, waiting for its proof. The network has agreed on what happened and the proposed block is just waiting a final proof. 

Anyone can prove it

Proving a block is its own job, and on Aztec, it belongs to no one in particular. A decentralized, permissionless set of provers competes to take a full epoch, a 32-block stretch of the chain, and compresses it into a single zero-knowledge proof of the entire epoch. Anyone with the hardware can run a prover and bid for the work. There is no privileged operator, no committee you have to trust, no outside network holding a key.

That openness is the whole point of a privacy layer. A system that protects your data but routes it through one trusted server has only moved the exposure rather than removed it. Aztec keeps proving permissionless and your private inputs on your device, thereby avoiding any exposure.

The economics land in the voter's favor too. As an L2 network, Aztec spreads the cost of that one L1 proof across thousands of transactions in the rollup, so a vote costs pennies, not the millions of gas a private proof would cost verified alone on Ethereum.

Settled on Ethereum, verifiable by anyone

A prover then posts the epoch proof to Ethereum's proven chain, and the Aztec state is final. Ethereum verifies one proof and inherits the correctness of everything inside it. Aztec extends Ethereum and settles to Ethereum, so your hybrid transaction carries Ethereum's security without carrying Ethereum's enforced transparency.

Anyone can now verify that the result is valid and that every counted vote was legitimate. No one can see how any individual voted. The tally is on the shared ledger where it belongs, and your ballot stayed yours the whole way through.

What this unlocks

For the voter, their ballot was never a broadcast. The candidate you chose stayed yours, with no record tying your wallet to a name for anyone to read later, and you can still check that your vote was counted and the result is honest. You took part without your choice becoming data for systems built to act on it.

For a founder, the election app in this walkthrough is easy to implement without needing to build extensive custom code. Secret ballots with a public, verifiable count, in one contract, is a product category that opens up only because the boundary is programmable. You can build governance, elections, and polls where people vote without fear and the result still proves itself. And of course you can build anything that requires both public and private state to work seamlessly together. 

For an infrastructure provider, the same machinery serves clients who need a result they can stand behind without exposing the people who produced it. Selective disclosure lets a client prove exactly what a counterparty needs to see, the count and the integrity of the process, and protect everything else, on their own terms. That is a guarantee a transparent chain cannot make.

A real vote needs two things at once: a secret ballot and a count anyone can check. A transparent chain makes you give up the first to get the second. On Aztec, you get both. The tally settled on Ethereum for anyone to verify, and how you voted stayed yours. The infrastructure is in place, what will you create with it? 

->Review the Aztec Basics

->Head to the docs and start building today

Explore by Topic
Noir
Noir
24 Jun
xx min read

Announcing the Noir awardees of the inaugural EF ZK Grants Wave

Aztec Labs is committed to enabling developers to build with ZK and unlock the full potential of this transformative technology. To that end, we built Noir, an open source Domain Specific Language for safe and seamless construction of privacy-preserving ZK proofs. We fund tooling, libraries, and applications that make Noir more accessible and enjoyable for developers.

Earlier this year, the Ethereum Foundation announced the first ZK Grants Round, a cofunded proactive grants round to encourage research and development for Zero-Knowledge proofs and standards for ZK L2s. Aztec Labs contributed US$150,000 to the US$900,000 prize pool alongside other projects such as Polygon, Scroll, Taiko, and zkSync. We sponsored this initiativeas a part of our commitment to support builders who are advancing ZK across dimensions including research, performance, tooling, and applications.

We were thrilled to see submissions to the ZK Grants Round from both new and existing Noir contributors. In this post, we want to highlight the ZK Grants Wave awardees for the Noir ecosystem to showcase what the community is working on and provide inspiration for how you could contribute.

Plonky2 backend for ACIR

Team: @eryxcoop, @manastech

Noir is back-end agnostic and its Arithmetic Circuit Intermediate Representation (ACIR) can be integrated with different proving backends. This project will enable Noir users to prove and verify their programs with Plonky2 technology, unlocking more possibilities to develop blockchain and ZK infrastructure with Noir. Meanwhile, it will also allow Plonky2 users to benefit from Noir’s developer-friendly abstractions, tooling, and growing sets of libraries, lowering the barrier of entry to the proving technology.

Detecting Private Information Leakage in Zero-Knowledge Applications

Team: @schaliasosvons, @theosotir

Noir abstracts away underlying cryptography so it’s accessible to a broader developer base. However, one risk of these abstractions is unintentionally leaking private variable information. This tool will apply static analysis, taint tracking, input generation, and SMT solving to detect privacy leaks in Noir program designs. Noir users can leverage this easy to use framework and debugging tool to identify, analyze and amend such leakages in their projects.

ZK Benchmarks

Team: @wz__ht

Performance benchmarking varies across different languages and proving systems. This project aims to produce benchmarking suites, articles, and a website that compares and informs developers about characteristics, performance, and tradeoffs between Noir-compatible and other proving backends in the ZK ecosystem.

ZK Treesitter

Team: @wz__ht

Noir reduces barriers for developers to use ZK with its simple and familiar Rust-like syntax. But a solid developer experience is more than just language design. It also depends on a strong ecosystem of developer tooling. This project will offer treesitter grammars that unlock features like syntax highlighting and code formatting for the language in more development environments like Helix and Neovim – providing Noir developers with more flexibility and choice.

Onboard users to verifiable KYC

Team: Neoxham, Lakonema2000, @0x18a6

Noir tooling and libraries are created to support and enable application developers who solve problems using ZK. This team will leverage Noir to create an educational end-to-end example of verifiable Know Your Customer (KYC) with compliance checks, and provide onboarding guides to increase adoption of the application.

We are grateful to the Ethereum Foundation for coordinating the ZK Grants Round and to the teams who submitted proposals. We look forward to seeing how the Noir community leverages these tools and resources to build the next wave of ZK powered applications.

If you’d like to learn more about Noir, read our docs and follow @NoirLang for more contribution opportunities coming soon.

Aztec Network
Aztec Network
11 Mar
xx min read

Client-side Proof Generation

TL;DR

The proof generation for a privacy-preserving zk-rollup differs a lot from that of a general-purpose zk-rollup. The reason for this is that there is specific data in a given transaction (processed by private functions) that we want to stay completely private. In this article, we explore the client-side proof generation used for proving private functions’ correct execution and explain how it differs from proof generation in general-purpose rollups.

Contents

  • What proofs are and how they work in general-purpose zk-rollups
  • How proofs work in Aztec
  • Proving functions’ correct execution
  • For public functions: rollup-side proof generation
  • For private functions: client-side proof generation
  • An example proof
  • How client-side proof generation decreases memory requirements
  • Appendix: other details of client-side proof generation.
  • Summary

What proofs are and how they work in general-purpose zk-rollups

Disclaimer: If you’re closely familiar with how zk-rollups work, feel free to skip this section.

Before we dive into proofs on Aztec, specifically the privacy-first nature of Aztec’s zk-rollup, let’s recap how proofs work on general-purpose zk-rollups.

When a stateful blockchain executes transactions, it conducts a state transition. If the state of the network was originally A, then a set of transactions (a block) is executed on the network, the state of the network is now B.

Rollups are stateful blockchains as well. They use proofs to ensure that the state transition was executed correctly. The proof is generated and verified for every block. All proofs are posted on L1, and anyone can re-verify them to ensure that the state transition was done correctly.

For a general-purpose zk-rollup, proof generation is very straightforward, as all data is public. Both the sequencer and the prover see all the transaction data, public states are public, and the data necessary to reconstruct each state transition is posted on L1.

How proofs work in Aztec

Aztec’s zk-rollups are a different story. As we mentioned in the previous article, in the Aztec network, there are two types of state: public and private.

Aztec smart contracts (written in Noir) are composed of two types of functions: private and public.

  • Private functions – user-owned state, client-side proof generation
  • Public functions – global/public state, rollup-side proof generation

For both of these, we need proof of correct execution. However, as the anatomy of private and public functions is pretty different, their proof generation is pretty different too.

As a brief overview of how Aztec smart contracts are executed: first, all private functions are executed and then all public functions are executed.

However, diving into the anatomy of Aztec smart contracts is outside the scope of this piece. To learn more about it, check the previous article.

Here, we will focus on the correct proof generation execution of private functions and why it is a crucial element of a privacy-first zk-rollup.

The concepts of private state and private functions in blockchain might seem a little unusual. The following map describes the path of this article, where we will shed some light on the difference between how proofs work for private and public states respectively.

Proving functions’ correct execution

For public functions: rollup-side proof generation

Let’s start by looking at public function execution, as it is more similar to other general-purpose zk-rollups.

Public state is the global state available to everyone. The sequencer executes public functions, while the prover generates the correct execution proof. In particular, the last step means that the function (written in Noir) is compiled in a specific type of program representation, which is then evaluated by a virtual machine (VM) circuit. Evaluated means that it will execute the set of instructions one by one, resulting in either a proof of correct execution or failure. The rollup-side prover can handle heavy computation as it is run on powerful hardware (i.e. not a smartphone or a computer browser as in the client-side case).

For private functions: client-side proof generation

Private state on the other hand is owned by users. When generating proof of a private transaction's correct execution, we want all data to stay private. It means we can’t have a third-party prover (as in the case of public state) because data would be subsequently exposed to the prover and thus no longer be private.

In the case of a private transaction, the transaction owner (the only one who is aware of the transaction data) should generate the proof on their own. That is, the proof of a private transaction's correct execution has to be generated client-side.

That means that every Aztec network user should be able to generate a proof on their smartphone or laptop browser. Furthermore, as an Aztec smart contract might be composed of a number of private functions, every Aztec network user should be able to generate a number of proofs (one proof for each private function).

On the rollup side, block proofs are generated using ZK-VM (ZK virtual machine). On the private side, there is no VM.

Instead, each private function is compiled into a static circuit on its own.

When we say “a circuit”, we’re referring to a table with some precomputed values filled in. This table describes the sequence of instructions (like MUL and ADD) to be executed during a particular run of the code.

There are a bunch of predefined relations between the rows and columns of the table, for example, copy constraints that state that the values of a number of wires are expected to be the same.

Let’s take a look at a quick example:

In the diagram above, we have two gates, Gate 1 (+) and Gate 2 (x). As we can see, z is both the output of Gate 1 (denoted as w3, wire 3) and the left input to Gate 2 (denoted as w4, wire 4). So, we need to ensure that the value of the output of Gate 1 is the same as the value of the left input of Gate 2. That is, that w3 = w4. That’s exactly what we call “checking copy constraints”.

When we say that the verifier verifies the circuit, we mean it checks that these predefined relations hold for all rows and columns.

An example proof

Disclaimer: the following example reflects the general logic in a simplified way. The real functions are much more complex.

Assume we have a function a2+b2=c2. The goal is to prove that equality holds for specific inputs and outputs. Assume a = 3, b = 4, c = 5.

As a piece of code, we can represent the function as the following:

When the function is executed, the result of each step is written down in a table. When this table is filled with the results of the specific function execution on specific values, it’s called an execution trace.

This is just a fragment of the table, with values and opcode names. However, to instruct the computer about which operation should be executed in which specific row, the opcode name is not enough; we need selectors.

Selectors are gates that refer to toggling operations (like an on/off switch). In our example, we will use a simplified Plonk equation with two selectors: qADD for the addition gate and qMUL for the multiplication gate. The simplified Plonk equation is: qMUL(a*b)+qADD(a+b)-c=0.

Turning them on and off, that is, assigning values 1 and 0, the equation will transform into different operations. For example, to perform the addition of a and b, we put qADD= 1, qMUL=0, so the equation is a+b-c =0.

So, for each performed operation, we also store in the table its selectors:

How client-side proof generation decrease memory requirements

In the case of private functions, as each function is compiled into a static circuit, all the required selectors are put into the table in advance. In particular, when the smart contract function is compiled, it outputs a verification key containing a set of selectors.

In the case of a smart contract, the circuit is orders of magnitude larger as it contains more columns with selectors for public function execution. Furthermore, there are more relation checks to be done. For example, one needs to check that the smart contract bytecode really does what it is expected to do (that is, that the turned selectors are turned according to the provided bytecode commitment).

As a mental model, you can think about a smart contract circuit as a table where 50 out of 70 columns are reserved for the selectors' lookup table. Storing the entire table requires a lot of memory.

Now you see the difference between circuit size for client-side and rollup-side proof generation: on the client-side, circuits are much smaller with lower memory and compute requirements. This is one of the key reasons why the proofs of private functions' correct execution can be generated on users’ devices.

Appendix: other details of client-side proof generation

  • To further decrease memory and computation requirements for the prover, we use a specific proving system, Honk, which is a highly optimized Plonk developed by Aztec Labs. Honk is a combination of Plonk-ish arithmetization, the sum-check protocol (which has some nice memory tricks), and a multilinear polynomial commitment scheme.
  • Some gadgets that may be added to Honk to make it even more efficiet include Goblin Plonk, a specific type of recursion developed by Aztec Labs, and ProtoGalaxy, developed by Liam Eagen and Ariel Gabizon.
  • Goblin Plonk allows a resource-constrained prover to construct a zk-snark with multiple layers of recursion. That perfectly fits the case of client-side proof generation, where a proof of each private function in a smart contract is an additional layer of the recursion. The trick is that expensive operations (such as Elliptic Curve operations) at each recursion layer are postponed to the last step instead of being executed at each. The recursion ends in one single proof for all the private functions in a smart contract.
  • This proof is then verified by the rollup circuit. The recursive verification of this proof is pretty resource intensive. However, as it is performed rollup-side, it has enough computation and memory resources.
  • ProtoGalaxy is a folding scheme that optimizes the recursive verifier work. It allows for folding multiple instances in one step, decreasing the verifier’s work in each folding step to a constant.
  • Diving into Honk and its optimizations is outside the scope of this article, but we promise to cover it soon in upcoming pieces.

Summary

Client-side proof generation is a pretty novel approach for the blockchain domain. However, for privacy-preserving solutions, it is an absolute must-have. Aztec Labs has spent years developing the protocol and cryptography architecture that make client-side proof generation performance feasible for the production stage.

You can help build it further.

Vision
Vision
7 Mar
xx min read

Regeneration: a Manifesto for an Autonomous Future

The following is written by Zac Williamson, with inspiration and advice from Arnaud Schenk.

My fellow companions, my decentralized brothers and sisters. I wish to tell you a story, about complicated people and their struggles to resolve the wreckage of their contradictions. It is a story of humanity.

We are at a unique point in history and stand at the threshold of two worlds. One world is a propagation of our present, a status quo antebellum with all of its associated joys and sorrows.

There is another door, one hidden from view except for those with the sight to see it. You and I are here because we see a unique vision of the future, one of high technology and high ideals, that advance human beings from their status as a commodity resource in a globalized world, to free actors imbued with autonomy and purpose, who bow to no one.

I want to articulate this vision and examine the forces that drive us. Despite our successes and dedication it is clear that our current achievements fall short of our aspirations. We must reconcile this.

Bitcoin is not yet a credible threat to traditional currencies. Paying for goods and services with cryptocurrency is a niche luxury for the technologically well-connected. Decentralized autonomous organizations (DAOs) are yet to govern anything that is not a cryptocurrency project. A notable exception was ConstitutionDAO, which immediately failed in its goals due to the intrinsic limitations of trustless blockchain networks.

There are missing pieces in the technological armaments we have fashioned. I want to show you the missing pieces. I want to go back to the roots: what are the systems and frameworks we want to disrupt? Which properties do blockchain networks need for us to forge a conspiracy against the present, and fight for our vision of the future?

Control Factions

Reaching back into prehistory, humanity has been waging a war against itself – a war that pits the freedom and autonomy of individuals against the safety and control of institutions.

We want to be free. We want to be safe. This is the eternal contradiction.

To acquire safety we bind ourselves to institutions. Within these institutions, control factions form. They metastasize and act to entrench their power and influence by monopolizing human agency. This triggers inevitable conflict and revolt, which acts to reset the equilibrium.

How best we can resolve the contradiction between freedom and safety is a function of social organization, the quality of which is gated behind technological innovation.

Blockchain is one such technology. To identify what we need, we must identify the weaknesses of the institutions we seek to undermine, and tailor our strengths against them.

The competency crisis

Control factions have a fatal weakness: they reject competence.

Competent people threaten individuals within entrenched power structures. A competent subordinate is a threat to your power and privileges. This is the so-called “dictator trap”, but the mechanics at play extend to all power structures, from the boards of mega-corporations to the local residents association. But it’s not a dictator trap, it is an institution trap.

Power craves legibility and predictability and will act on these desires by exerting control – limiting agency and freedom of action.

Re-distributing institutional control

We want to undermine institutional control, and redistribute control down to smaller units of organization.

Blockchain technology enables such radical new forms of social organization that fall outside the frameworks of traditional institutions.

We possess a keystone technology that enables mass peer-to-peer coordination, initially of cryptocurrency assets but this can be generalized to anything with perceived value that can be given a digital fingerprint.

Blockchain networks have radically different incentive mechanisms to traditional modes of social organization.

Because blockchains are coordination engines. They enable individuals to coordinate on how to deploy their collective resources. This type of mass-coordination of personal resources is unique and will subtly act to profoundly re-distribute the existing power structures of the present.

Why? Blockchains weaken the fundamental value propositions of vertically integrated companies that extract a profit from information asymmetries. Individuals whose skills serve large institutions can more easily decide for themselves how best to apply their skills, without the need for the institution’s support frameworks. As a coordination engine, blockchain networks can efficiently combine the skills and capital required to execute grand ideas, as well as provide a digital market for resulting products.

A global marketplace of programmable money is one with profound information transparency. The ability of independent groups to analyze the market enables great efficiency and reduces information asymmetries. Though, does not delete them entirely.

In short, blockchain networks are pro-competency. They allow individuals to decide for themselves how their skills can best be utilized and deployed, instead of having that decided for them by a control faction. Competent people add value to the network and in doing so, provide another composable brick that others can use in their constructions. The raw incentives create a positive-sum game.

Missing pieces

What are the missing pieces?

The great difficulty in realizing our vision is the limited ability of current blockchains to reach into the real world.

We are not our online avatars. We exist in a physical space and we have physical needs that must be satisfied. We are bound to networks of obligation and responsibility that societies depend upon to maintain social order. We cannot live in an NFT.

The real world matters. Without a way of linking real-world identities to blockchains, the grand cypherpunk vision for blockchain can never be fully realized – only a neutered form of primitive electronic sovereignty.

The new information networks: composable privacy

The new information networks we are building lack a key ingredient: composable privacy.

By using novel cryptography, we can turn blockchains into encrypted ledgers where transactions hide their execution from observers. Identities can be encrypted, but still used to prove statements about the user, and without involving an additional institutional third party. e.g. “I have a U.S. passport”, “I have a digital driving license”, “I have a Twitter account with over 1,000 followers”, “I signed in with a Google account”.

The effect of this is to build trust infrastructure that allows human beings to iteratively build trust between themselves and to do so rapidly and at scale.

Programmable private blockchains stand to usher in a revolution in how distributed systems can be used. Without strong identity guarantees, the only workable governance mechanisms for distributed on-chain organizations are autocracy and plutocracy.

However, if past actions can be uniquely tied to a cryptocurrency account, it is possible to identify key stakeholders and to give them an accelerated role in governance. That enables a much more democratic architecture of governance systems.

Privacy technology is required to turn blockchains into the coordination engines they were always destined to be.

The future we are building does not outright destroy existing systems of control – it breaks them apart and replicates these systems on a smaller scale. Lower barriers to entry lead to greater competition and market fragmentation and act to limit the ability of distributed organizations to consolidate power.

Because coordination engines are pro-competency.

Privacy for the user, transparency for the protocol

There is a phrase I think we will hear much of over the coming years: privacy for the user, transparency for the protocol.

The capabilities of private programmable blockchains and the outcomes they enable are not commonly understood. A private blockchain is not one where all information and data are intrinsically hidden. They are hybrid systems where public and private data coexist. Application designers and users can choose which data is hidden.  

Efficient markets require data transparency. Data relating to identity requires data confidentiality. The solution is applications where information that relates to assets is public, and information relating to users (e.g. who owns said assets) is private.

To create a privacy-preserving ecosystem it must be possible for confidential, transparent, and hybrid applications to directly interact with one another. Privacy is not an aftermarket add-on to be bolted onto a few select applications. Full composability is essential to develop a rich ecosystem.

Composability enables trust-building networks by allowing individuals to put core aspects of themselves on-chain, disclosing it only selectively and enabling distributed protocols to use these capabilities in a composable permissionless manner, without leaking information. Who are you? What have you done? What do you want to do? With privacy, we can disclose this information to smart contracts and hide it from people. These will form core primitives of our new information networks.

I have spent the last 6 years building exactly this, through building Aztec. Crafting the missing ingredient, privacy, via cutting-edge cryptography, zero-knowledge proofs, and raw engineering.  

Values of the new information networks

Networks have values that are independent of their creators. Networks live or die on the quality of their network effects. This incentive gives network participants a shared motivation to expand the network. The more nodes that exist, the greater the value individual nodes can extract from the network. The manner in which the network changes itself to act on these motivations defines its intrinsic values.

What are the intrinsic values of permissionless programmable privacy networks like Aztec? We can derive these from the fundamental value proposition – to expose a rich ecosystem of composable, confidential applications, and to do this as a permissionless, decentralized network. This enables individuals and small groups to compete in industries dominated by large players leveraging large information asymmetries.

Such networks are, at their very core, pro-competency. If you have something useful to add to the network, you can. If you want to use existing network components in your product, go right ahead. No need to ask for permission from the network.

From this starting point we can anticipate the cycles of action and reaction that will drive networks like Aztec to adopt the following values over their lives:

  • They are pro-emergence and pluralistic.
  • They strongly desire individual autonomy and freedom of action.
  • They are fiercely anti-elite, but not necessarily anti-elitism.
  • Finally, they seek to undermine traditional frameworks of control and subjugation used to promote institutional stability.

Blockchain networks grow by harnessing the industry and enterprise of as many human souls as they can get their hands on.  

Without mechanisms of coercion to fall back on, the network must ensure a positive-sum game for network participants who add value. These also happen to be values that I believe I strongly hold. This is not a coincidence. I started in web3 seven years ago building a marketplace for corporate debt on Ethereum and by degrees ended up building a distributed programmable privacy network on Ethereum. This was not due to some grand design but, I think, the cumulative effects of seven years of following my impulses. To find a place of belonging.

This feeling is something you may share – that the frameworks and systems produced by our societies offer none of us a true sense of belonging and purpose. But here, amongst our companions, we have found belonging through building a shared vision of a radical new world.

The road ahead

There is a long road to walk to realize the ambitions of the new information networks. The technology is barely capable and challenging to build. The architecture is novel and challenging to design. Convincing people to build on radical foundations to bootstrap a market is challenging. Building competitive infrastructure and tooling is challenging.

The challenge is irrelevant. We cannot become a generation scorned by our descendants for squandering the opportunity of a lifetime.

We will build and deploy the new information networks and by degrees will learn how to use them to chip away at the inequities of the status quo, and the social order that upholds it.

Equipped with such armaments and driven by our ideals, we will pull our ideas into reality. Together, we will forge our digital Eden.

Noir
Noir
3 Jan
xx min read

Interview with Kev Wedderburn, Father of Noir

Kev Wedderburn is the father, architect, and team lead of Noir, a universal zero knowledge circuit writing language funded by Aztec Labs.

We're excited to bring you this interview and profile of the man and mystery behind the DSL creating a step-function change in the accessibility of ZK programs.

Alyssa: Hey Kev! Thanks so much for your time, I’d love to give readers a snapshot of your journey into web3 and Aztec Labs, as well as your focus on the Noir team.

Kev: Sure! Let’s jump in.

Alyssa: Can you start by sharing your web2 background?

Kev: Yes. I started out as a front-end developer, then moved into app development.

I built a social media site for books. Then, a janky music-sharing app that would check your playlist, then check my playlist, then if our playlists overlapped enough, it would recommend each of us songs on each other's playlist (this was before Spotify became Spotify I think).

Alyssa: How’d app development lead you to going full-time web3?

Kev: While transitioning to crypto, I made a tax app that scanned your bitcoin QR code and told you how much tax you owed.

From there, I started doing tutorial videos focused on smart contracts. I wanted to do one for a particular blockchain, and it turned out that they didn’t have a well-functioning wallet. So that’s actually what led to my entry into the web3 space. I didn’t end up finishing that tutorial, I just went on to build the wallet myself.

Alyssa: And this work led to your first formal web3 role?

Kev: Eventually, yes. While I was working on an improved wallet, I noticed the node that the original wallet was interacting with wasn’t that great either. So once the new wallet was finished, I moved on to creating a node in Golang (the wallet was also originally built in Golang).

After I finished the node, I got recruited by a privacy-focused project. And they asked me to build a node for their privacy network.

Once I dug deeper, it turned out they didn’t have a proving system. So then I started learning cryptography to implement a type of ZK proof called bulletproofs — state of the art at the time.

Alyssa: And you’ve primarily worked on privacy within web3 ever since, is that right?

Kev: Yes, I worked for several other privacy blockchains prior to Aztec, such as Monero. At Monero, I pivoted from implementing Bulletproofs to Plonk for increased proving speed, but noticed it was very challenging to program on top of Plonk.

The Plonk constraint system and proving system both have nice properties, but the UX was really bad. So Kobi Gurkan from Geometry Research, and Barry Whitehat from the Ethereum Foundation asked if I wanted to make a compiler — I guess they saw that I was pretty active within Plonk and cryptography in general.

Alyssa: Had you built one before?

Kev: At the time, I didn’t know much about compilers at all, so it was exciting to figure out what the compiler I’d build would look like, what other compilers were doing, and how to make a compiler with the safety guarantees needed for zero knowledge proofs.

That was the beginning of what we now call Noir, and I’ve been at Aztec since.

Alyssa: Wow, okay, so you’ve been with the Noir project since the beginning of Noir’s existence?

Kev: Yeah, exactly.

Alyssa: Amazing, congrats on all the progress you and the team have made. And what about getting into web3 in the first place? Was it through engineering, or your own interest in cryptocurrency? How did that look?

Kev: I first looked at Bitcoin in university, but was deterred by the codebase being challenging to read. But I wanted to learn Bitcoin and teach people about it. Back then, everything was a bit scammy. I even created a Bitcoin book…

Alyssa: Going back to Noir, how do you feel about the experience of learning the language you helped build? Is it intuitive for developers?

Kev: I can tend to over-criticize the things I do. But Noir’s in a solid place. There’s not much to really compare it to….there are other zkDSLs, but they give different guarantees for the most part. For example, Noir provides devs with a high-level language that aims not to sacrifice performance and safety, while Circom gives devs very little safety but allows them to do anything. There are pros and cons to both of these approaches.

The more control you give to a developer, the more powerful things they can do, but they can also easily make mistakes because the compiler is no longer holding your hand or stopping you from doing something potentially dangerous.

But yes, Noir is in a good place for developers to use. There’s still a lot we want to put into the language to make it comparable to common programming languages in terms of UX. But we’re well on our way.

Alyssa: And what about just being on the Aztec Labs team in general, and maybe even the Noir team within Aztec Labs? What’s that like? What do you enjoy about it?

Kev: The Aztec team is cross-functional and fluid, meaning that even though you’re on the Noir team, or the tooling team, or the engineering team, you can touch other parts of the stack. So that’s great about being at Aztec.

The fun thing about the Noir team in particular is that there are so many challenges we have yet to solve. We’ve solved quite a lot of them, but there’s still a lot we’re excited to work on like continuing to improve the UX, as I mentioned.

Alyssa: Love that answer as I know there’s a job opening on the Noir team, so someone joining can have exposure beyond understanding their specific role.

Kev: In fact, we encourage that, if you’re on tooling and you want to create something and the compiler just doesn’t seem to be fit to do what you want, feel free to start some print or tasks to modify the compiler. We’re always open to new ideas.

Alyssa: Really cool, that’s great. And what about beyond web3, any general interests or hobbies?

Kev: Generally speaking, I really like maths. I also used to sing and play guitar for quite a while, and I exercise a lot these days.

Alyssa: Thanks again for the chat, great learning a bit more about your work, Kev!

Kev: Thank you!

Get started with Noir

We think Noir has the best syntax, most modularity, and best ecosystem of any ZK language. But don't take our word for it.

Get started with Noir at noir-lang.org.