Aztec Network
Mar 18th, 2021
## min read

Aztec’s ZK-ZK-Rollup, looking behind the cryptocurtain

Aztec's zk-zk rollup is a game-changer, blending privacy with scalability for a unique blockchain experience.

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Written by
Zac Williamson
Edited by

At Aztec we’re excited to have launched zk.money this week, enabling efficient, completely private transactions on the Ethereum blockchain.

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So, it seems you noticed ... Yes, Private Layer 2 ZK-Rollup has arrived on Ethereum | https://t.co/p2DxzB4sm9

This is something we’ve building towards for almost 3 years now.

The privacy our users enjoy does not rely on trusted third parties or additional consensus algorithms. The security of our system is backed up by ironclad zero-knowledge cryptography, with the consensus of our network being derived directly from the strengh of Ethereum’s consensus protocol via our zero-knowledge proof verification smart contracts.

This is the first time a privacy-preserving rollup has been deployed to Ethereum, or any other public blockchain for that matter.

Getting to this point has been quite the adventure for us. When you trigger a private send from zk.money, your computer will grind through some of the most advanced number theoretic computations ever pushed through a web browser.

We’ve had to design a lot of new tech to pull this idea into the world. From inventing the cryptographic protocol we use and building an optimized proving system, to the backend server that aggregates and processes zero-knowledge transaction. This article is a dive into the tech behind our private ZK-rollup and its inner workings.

What is a private ZK-rollup?

Zero-Knowledge-rollups are a way of scaling Ethereum. Instead of having the blockchain processing every transaction in a block, the block’s transaction inputs and outputs are sent to Ethereum, along with a zero-knowledge proof that the transaction outputs have been correctly computed from the inputs. This reduces the computational burden on the network and reduces the amount of smart contract storage data that must be modified.

Traditional ZK-rollups aren’t privacy preserving despite their name; the ‘zero-knowledge’ refers to using ZK-Snarks for scaling only.

Private ZK-rollups are a different beast. As well as providing the scaling benefits, the transaction inputs/outputs are encrypted. The zero-knowledge proof that proves the correctness of every transaction also proves that the encrypted data was correctly derived from the non-encrypted ‘plaintext’ data. But the plaintext is known only to the users that constructed their private transactions.

The rollup cannot simply process a list of transactions like before, it must verify a list of zero-knowledge proofs that each validate a private transaction. (This extra layer of zero-knowledge proof verification is why they’re called ‘ZK-ZK-rollups’).

The result is reduced-cost transactions with full transaction privacy, even from the entity making the rollup! Both the identities of senders/recipients are hidden, as well as the values being transferred.

Despite this, users of the protocol can have complete confidence in the correctness of transactions (no double spending etc), because only legitimate transactions can produce a valid zero-knowledge proof of correctness.

Plonk: the world’s fastest universal ZK-SNARK

In theory ZK-ZK-rollups have been known about for several years, but nobody has managed to deploy one in practice, until now. There were an immense number of technical hurdles we had to overcome to get to this point, not least of all having to design our own ZK-SNARK protocol to get the job done!

Plonk is our state-of-the art ZK-SNARK, developed in-house by our chief scientist Ariel Gabizon and CTO Zac Williamson. Its fast proving times, expressive method of circuit arithmetisation and lack of circuit-specific trusted setups makes it ideal for blockchains. The Electric Coin Company, Mina Protocol, Matter Labs, Dusk Network and more are all using Plonk in their latest projects.

Aztec’s ZK-ZK-rollup architecture

Our architecture is composed of two programs that we have encoded into ZK-SNARK ‘circuits’: A privacy circuit and a rollup circuit.

The privacy circuit proves the correctness of a single private transaction. It is constructed by users that want to send private transactions, directly on their hardware to ensure no secrets are leaked.

The rollup circuit validates the correctness of a batch of privacy proofs (currently 128) and updates the rollup’s database with the new encrypted transaction data.

The rollup proofs are constructed by a rollup provider, a 3rd party that has access to significant computing resources (for the moment, Aztec are the rollup provider. Longer term we plan to decentralize the rollup service). The rollup provider is completely untrusted. They do not have access to any user data and only see the encrypted outputs of privacy proofs. This also makes it impossible to launch selective censorship attacks, because all transactions look like uniform random numbers.

Join-split private transactions are aggregated in batches of 32 by a rollup circuit. Rollup proofs are aggregated by a rollup-of-rollups circuit. This tiered aggregation structure allows us to scale to large block sizes and massively parallelize proof construction.

Building a ZK-ZK-rollup

Both the privacy circuit and the rollup circuit have two major challenges associated with them:

1. The privacy proof must be computed by the user, it cannot be delegated to a 3rd party.

2. The rollup circuit must efficiently verify the correctness of hundreds of privacy proofs.

The former is challenging because users are likely to interact with our software in a web browser. Executing cryptography code in a web browser is approximately 8x slower than running native compiled code, due to the WebAssembly specification lacking an opcode for full-width 64x64-to-128-bit multiplication.

The rollup circuit requires recursion, the ability to verify ZK-SNARK proofs inside ZK-SNARK circuits. Until recently, the consensus was that this required cryptographic primitives that are not supported by the Ethereum specification!

Both problems boil down to the fact that constructing ZK-SNARK proofs are slow. Basic arithmetic operations in a circuit must be converted into tens of thousands of 256-bit big-integer multiplications.

Previously existing ZK-SNARKs simply were not efficient enough to serve our needs and/or had unacceptable security trade-offs (like requiring trusted setup ceremonies for every circuit).

We put together Plonk to solve these problems. Plonk was the world’s first practical, fully succinct universal ZK-SNARK. Its ‘universal’ because only one trusted setup is required for every Plonk circuit (we completed our trusted setup ceremony, ignition, in 2020).

We have not been idle since then, and our software uses a much-improved version of our protocol, TurboPlonk.

Turbocharging Plonk

TurboPlonk is a dramatically enhanced version of our original Plonk protocol.Existing SNARK systems can only perform basic arithmetic operations: adding and multiplying prime field elements together.

This is a bit like having to work with a computer whose ALU only has `ADD` and `MUL` instructions! This is one of the reasons why SNARK proofs are so slow to construct — transforming a program into a circuit blows up the instruction count.

Put in context, existing SNARK arithmetic is about as complex as the kind of math you could program on a 1961 Programma 101.

A Programma 101. If we compare the progress of ZK-SNARK tech to the progress of computing tech, we are probably about here…

This restriction is because of the way the arithmetisation of traditional SNARKs is constructed. Elliptic curves are homomorphically additive ([A] + [B] = [A + B]). General homomorphic multiplication is not possible, but the bilinear-pairing enables a single homomorphic multiplication by the one way mapping into the target group.

Most ZK-SNARKs have arithmetic that directly maps to the available operations on an elliptic curve. This is codified into the Rank One Constraint System abstraction (R1CS), a method of defining circuits by creating ‘constraints’ composed of many additions, combined with a single multiplication. The current fastest R1CS-based proving system is the non-universal Groth16, currently used by Zcash.

Plonk and TurboPlonk are different. Their use of polynomial commitment schemes divorces their arithmetic from the limitations of elliptic curve group operations. i.e., we can multiply more than once per ‘constraint’.

In TurboPlonk, we use this flexibility to implement what we’re calling ‘custom gates’. Instead of just ADD and MUL gates, we have added gates that can do the following:* 2-bits of an XOR op* 2-bits of an AND op* 8-bit range checks* 2-bits of a Pedersen hash function

Still primitive by traditional standards, but at least the addition of logic operations moves us out of programmable calculator territory.

Efficient range checks, Pedersen hashes and logic operations are the bread and butter of the type of cryptography required in modern ZK-SNARK circuits. They make TurboPlonk not just competitive with non-universal proving systems like Groth16, but in many cases significantly faster.

Building the rollup proof and achieving recursion

Verifying a SNARK proof inside another SNARK circuit is traditionally a profoundly difficult task. SNARK circuits can only perform operations modulo a specific prime number p, a number defined by the elliptic curve you are using.

Verifying a SNARK proof requires elliptic curve arithmetic modulo a different prime number q. If you are using a single elliptic curve, qmust be different to pfor the curve to be secure!

How does one perform arithmetic modulo qwhen all your calculations are mod p? The ‘brute force’ approach requires emulating binary arithmetic using your ‘mod p’ arithmetic. Literally proving that individual wires in your circuit are 0 or 1, and assembling larger integers out of your bits.

You can then emulate your ‘mod q’ arithmetic using your emulated binary arithmetic.

This comes at a huge cost, the resulting system requires a revolting number of range checks, millions of them in fact.

This is the reason why recursion has proven to be a brick wall that blocks the deployment of advanced zk circuits on Ethereum. Existing solutions to the problem (e.g. Halo) utilize elegant number-theoretic constructions to get around this wall, but they require cryptographic operations that are not available within Ethereum smart contracts.

Fortunately, we designed TurboPlonk to be extremely good at efficient range checks (16x better than regular Plonk), to the point that we can sledgehammer our way through the problem and use the emulated field arithmetic approach.

We published our recursive construction in April last year. It is the only practical method of achieving recursive ZK-SNARKs on Ethereum to-date.

Achieving full privacy

Achieving full privacy in a rollup presents some unique challenges, other than the recursive SNARK problem.

We need to ensure that when a user spends a note, the spend transaction cannot be linked to any existing note.

This is achieved by using a set of ‘nullifiers’. Each nullifier represents a spent note. The encryption algorithm used to create nullifiers is different to note encryptions. This prevents linkability between notes and nullifiers.

Nullifier sets are problematic, however. To prove a note has **not** yet been spent, one needs to serve a *proof of non-membership*. To ensure our non-membership proofs have 128-bits of security, we need our nullifier Merkle tree to have a depth of 256!

Traditionally this would make membership and non-membership proofs of the nullifier set inordinately expensive. However, because of our custom Pedersen hash gate, our Pedersen hashes are 5x more efficient than systems that use R1CS and 18x more efficient than regular Plonk.

The result is that we can support depth-256 nullifier sets within our rollup architecture, which is not something that has been achieved to date.

Moreover, we are able to do this with a traditional well studied hash function. The collision-resistant properties of Pedersen hashes are well understood and we use Blake2s hashes whenever we need to model the hash function as a random oracle. We chose not use more recent SNARK-friendly hash functions due to the relative lack of cryptanalysis that has been performed on them, compared to the alternatives.

Building privacy proofs in a web browser

To give some scale to the problem, Zcash proofs can be generated in ~3 seconds on modern hardware. Universal SNARKs traditionally are about 10x slower than the Groth16 system currently used by Zcash. On top of that, we are using WebAssembly which is 8x slower than native code. That’s also assuming you can get multithreading working in the browser without browser support for WebAssembly threads (disabled after Spectre/Meltdown). Under these assumptions even a basic private transaction proof would take around 4 minutes to construct. Ouch!

But it gets worse! Our privacy circuit is larger than the Zcash circuits. We felt it was important to support social recovery of lost accounts, which requires an account management subcircuit within our privacy circuit. If we encoded our circuit in the traditional R1CS form, it would have approximately 260,000 constraints and would take up to *8 minutes* to prove in a browser.

Fortunately, TurboPlonk is up to the challenge. Our ability to efficiently evaluate hashes and bitwise logic operations crushes down the constraint count of our circuits to a more reasonable 65,535. We combined this with prover algorithms that are optimized for WebAssembly and a javascript SDK that implements a multithreaded variant of our WebAssembly prover using web workers.

On top of that, we have put together a new elliptic curve multi-scalar multipliation algorithm. It was, to our knowledge, the first time this algorithm had been implemented. It is also the fastest algorithm that currently exists for large multi-scalar multiplications.

A new algorithm for ecc multi-scalar multiplication

Traditional ecc multiplication algorithms represent elliptic curve points in 3-dimensions with `X, Y, Z` coordinates. This is in contrast to ‘affine’ coordinates, which just use an `X` and `Y` coordinate.

ECC operations can be split up into 3 distinct types: field additions, field multiplications and field inversions.

The problem with affine coordinates, is that elliptic curve addition requires 3 field multiplications and a field inversion. Inversions are about 250x more expensive than multiplications.

affine point addition (3 field muls + 1 field inversion)
jacobian point addition (16 field muls)

By adding a Z-coordinate, the field inversion is removed at the expense of adding 8 field multiplications.

Traditional ecc multiplication algorithms use the 3-coordinate representation because of this.

However, we exclusively work in affine coordinates. Our algorithms are constructed so that, when we need to perform point additions, we must perform many linearly independent additions. For each set of point additions, we use Montgomery’s batch inversion trick to compute all the required field inversions with a single field inversion, amortising away its high cost.

The result is an algorithm that is 30% faster than those that do not this technique.

Putting it all together

The result of this is that, on modern laptops, our privacy proof can be computed in a web browser in only 10 seconds. Advanced private transactions have finally become practical in a web-browser. Our latest in-development tech will continue to drop this number.

Looking into the future

Private transactions are just the tip of the iceberg. The most important goal for us over the next year is to support full programmability. Only by giving developers the tools to develop their own custom protocols and transaction flows will our vision of programmable private digital currencies be realised.

Our final architecture will support fully programmable privacy-preserving smart contracts, written in our new ZK-SNARK programming language Noir. Noir has been designed from the ground up to be optimized for compiling to our proving systems and for making privacy easy to work with.

The end goal is to support an active ecosystem of private cryptocurrencies, each with the ability to interface with existing L1 and L2 protocols, as well as DeFi protocols deployed directly onto Aztec’s rollup.

We have also not been idle with our R&D. Our latest cryptosystem, UltraPlonk, is close to deployment and will power our upgraded protocol architecture. UltraPlonk utilizes our latest plookup research, which enables efficient look-up tables within Plonk circuits. This is a major breakthrough that enables ZK-SNARK circuits to efficiently implement traditional algorithms that do not rely on prime-field arithmetic (e.g. AES128 encryption, SHA hashes, even basic things like integer arithmetic). It also allows us to efficiently add traditional memory abstractions into Noir, something completely foreign to existing proving systems.

We’re planning a full article that outlines our future plans and roadmap in detail. Stay tuned for more details!

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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

Aztec Network
Aztec Network
23 Jun
xx min read

The Devil's Bargain - Privacy Without Credible Neutrality

Crypto is in a long night. It is no secret that the industry is facing challenging circumstances and there has been a clear consolidation of the industry. Right now we are seeing a focus on real traction, demonstrable value projects shipping practical solutions that will meaningfully reach users. 

Some of that discipline is overdue. However, in times like these the properties that made crypto structurally different begin to look expendable. Decentralization slows you down. It makes upgrades harder. It makes institutional sales harder. It removes the control surfaces that the existing financial world knows how to buy.

We used to accept those costs as the price of building something durable. But, in a famine, they look like unaffordable affectations. Discarding them wholesale, however, is like selling the land out from under our feet.

Permissionless, uncensorable transaction networks with rich composability - this is the clay from which our industry was grown. The long term commercial health of our industry depends on preserving these properties in an age of privacy and institutional adoption.

These trade-offs become more challenging and pernicious when privacy is involved. Privacy is the narrative for crypto in 2026, and for good reason. It’s the missing piece that will deliver the traction and real use-cases that the industry so desperately needs. 

The challenges of decentralization multiply under the constraints of privacy and what we are seeing in the industry is not a pivot, but a complete capitulation of all of the differentiable value that made crypto valuable.

I have spent nearly a decade building a network that marries programmable privacy with decentralization. A network where users keep their data, where applications are composable with one another, where transactions can settle without a privileged party learning everyone’s business or deciding which products are allowed to exist. That required new cryptography, new programming models, new state architecture, new wallets, and a fairly insane number of tradeoffs that are invisible until you try to build the thing yourself. There are easier products to ship. 

A centralized privacy service can give institutions something legible quickly, replicating how the existing financial sector works: a responsible operator, a viewing key, a way to block transactions, a way to explain the whole thing to a risk committee. Some of these products will be useful. Some will be good businesses. But they are not the thing we came here to build.

The Devil’s Bargain

Institutional and enterprise adoption is one of the core growth areas in this crypto-winter and the playbook is simple: use the language of crypto as a skin-suit to sell products and services that pattern match onto existing financial rails, with their need for complete visibility, censorship, centralized network operators and all of the liabilities this incurs.

This is a tempting bargain because it shortens the path to adoption. It gives buyers and regulators a shape they understand. A company. A contract. A switch. But the moment you accept that bargain, the system changes character. It may still be encrypted. It may still contain proofs. It may still call itself private. But, it now behaves like and is an operated service. 

There is a party with privileged knowledge and privileged control. Builders must shape themselves around it. Institutions negotiate with it. Regulators may pressure it. Attackers target it. Users ultimately depend on it. By a backdoor I mean something specific: a network or protocol-level viewing key where the product developer does not control who can see their users’ data, especially when paired with network-level controls that can block transactions or ban smart contracts entirely. I do not mean application-level controls. I do not mean user-authorised disclosure. I do not mean a dapp deciding that users must prove something before using it. Regulated applications will need rules. The issue is that the disclosure boundary of your application belongs to somebody else, and the same layer that sees can also decide whether your users are allowed to transact. In short, users lack a platform that has credible neutrality.

The Platform Risk

Privacy on top of centralized rails is fatal. If one party can see everything and stop anything, that party may be treated as responsible for seeing and stopping.

This compounds into substantial platform risk. If an entity builds on top of such a system they must surrender visibility and control to the network operator to satisfy their liabilities without consideration for yours. Decentralization and ultimately credible neutrality is the difference between whether you own durable infrastructure or are renting a service whose rules can change on a whim. Worse, you cannot “just build things”. For novel transaction flows approval must be sought and granted. Tell me, would Ethereum have grown if every smart contract deployment required approval from the Ethereum Foundation?

Privacy needs the same freedom. A private credit market, for example, touches identity, collateral, repayment history, payment flows, liquidation logic, lender disclosures, auditor access and borrower privacy. If every component lives inside a different permissioned service, each with its own operator and viewing assumptions, that is a bureaucratic friction that negates blockchain’s core value proposition; composability.

A decentralized and credibly neutral privacy network prevents the settlement layer from becoming the single place where all surveillance and censorship obligations naturally accumulate. It allows product developers to scope their code to satisfy their own narrow requirements without consideration for the obligations of a centralized operator.

Building for credible neutrality

A lot of today’s privacy narrative treats architecture as if it were a detail. It is not. You cannot take a transparent ledger, staple confidentiality onto the edge, add a viewing key for comfort, and expect to get programmable private infrastructure.

If the state model is not private from the ground up you get wrappers, third party tools, data custodians, ad hoc disclosure paths and a pile of assumptions that every application drags into the next. Developers do not get a normal programming model where private contracts can call private contracts and users keep state on their own devices. They do not get composability.

The difference matters. In a real private execution environment, users generate transactions locally. They do not outsource their intent to a third party who learns what they are doing. Private contracts interact through a state model designed for privacy. The network settles proofs without becoming the party that knows everyone’s business. Privacy is part of the architecture.

This is why Aztec has taken so long. We built something that makes programmable private state and decentralised settlement live inside the same system. That means proving systems that run on consumer hardware, a transaction architecture built around local private execution, and a programming model where privacy is idiomatic and just works out of the box.

A centralized service can skip much of this. It can hold the key, run the prover, approve the flow and call the result privacy. It gets to market faster because it is not trying to arrive at the same place.

The edge

Adding decentralization does not make obligations disappear. Applications, issuers, frontends, custodians and regulated businesses will continue to exist in a web of obligations and responsibilities. Anyone pretending otherwise is unserious.

The question is where those obligations live. If they are pushed into the settlement layer, the settlement layer is no longer credibly neutral. It needs visibility into everyone and controls over everyone. 

The better answer is selective disclosure. Users and applications should prove specific facts to specific parties for specific purposes. A regulated application may need to know that a user passed a check, that a transaction satisfies a policy, or that an auditor can inspect a particular flow. None of that requires the base network to hold a permanent key into everyone’s activity.

This will be harder to explain to the existing world. New infrastructure always fails to fit the categories built for the old infrastructure. Bitcoin did not arrive as a neatly regulated bank product. Ethereum did not wait for every lawyer to understand smart contracts. Stablecoins and DeFi forced institutions, regulators and users to develop new language around rails that kept existing.

If the standard for privacy infrastructure is to plug into the old world without changing anything, the answer will always be a service with a backdoor. And the result will be to catch crumbs falling from the tables of the old world.

The market worth building

The market we should be building is, well, a market. A private financial system that compounds: assets, liquidity, identity, credentials, credit and applications interacting through a shared settlement layer without forcing users to surrender their data to whoever sits in the middle. 

Traditional finance is built out of vertically integrated information silos. Those silos are its moat. Banks, exchanges, custodians, payment processors and data brokers all benefit from controlling the information that flows through them. A global private settlement layer attacks that advantage directly. It lets liquidity and credentials move while outsourcing information custody to neutral cryptographic infrastructure. 

A company wants a moat. A settlement layer wants surface area. A permissioned privacy provider can ration access, raise fees, exclude applications, shape disclosure rules and define acceptable use around its own risk tolerance. These are products pretending to be networks, and not durable financial infrastructure. What bothers me is this compounding category confusion. Networks adding protocol-level viewing keys and transaction controls are using the same language as decentralised programmable privacy, and commentators are treating them as variations of the same thing. They are not.

We have spent nine years walking the hard road. Now, just as we are close, the market has lost faith. Everyone is reaching for whatever lifeline looks immediate. Some of those lifelines will be real. Some will make money. But if crypto responds to its long night by rebuilding financial privacy as permissioned services, then we will have survived by surrendering the property that made the industry worth building.

Markets can grow when the platform is removed from the position where it can dictate the rules. It would be perverse to forget that lesson while building privacy, the domain where control over information matters most.

The land we till

Crypto is in a famine. The land is struggling. We could sell our land for a pittance and survive the season. But the famine will pass, and when it does the land will blossom again. Without the land we are nothing.

We have struggled immensely to create a permissionless network that can marry privacy with decentralisation: an indestructible network whose users cannot be surveilled and whose transactions cannot be censored. This is the soil we have to grow our crops. To surrender a backdoor or a centralized operator for temporary relief is to sell our land for the price of a stablecoin. And we cannot sell the land.


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Aztec Network
Aztec Network
2 Jun
xx min read

Who controls your privacy off-switch?

Privacy has become a baseline requirement for L1s and L2s who care about bringing real-world users onchain. Users don't want their activity broadcast to competitors or the general public, but applications operating at scale also need some form of auditability, whether for regulators, compliance requirements, or tax reporting. Selective disclosure resolves that tension: privacy by default, with the ability to prove specific facts when required. What separates these networks is not whether they offer that switch, but who gets to hold it.

Aztec, Canton, Starknet, Tempo, and zkSync all offer some form of privacy with selective disclosure, but under the hood they make fundamentally different architectural decisions about who can see your data and who can turn your privacy off. Those decisions determine whether your privacy stays under your own control or sits behind a switch that someone else operates.

Three questions reveal where these networks actually diverge:

  1. Who sees your data?
  2. Who can prove the network followed its own rules?
  3. Who controls when something gets disclosed?

The answers determine whether your privacy off-switch is held by a policy, by an operator's good behavior, or by you alone through a cryptographic proof. As you'll see in this post, there are legitimate reasons to use each one with different tradeoffs. Aztec is the only network, however, where that switch stays in the user's hands, answering all three questions without putting a permissioned set of operators or a standing viewing key in control of your privacy. That gives developers the flexibility to build apps that comply with applicable laws while still keeping full privacy under the user's control.

This article will compare the privacy approaches of Aztec, Canton, Starknet, Tempo, and zkSync to give developers insight into the privacy tradeoffs of each network.

TL;DR

Here’s how each network handles the selective disclosure privacy off-switch, and who has control over your privacy: 

  • Aztec: Only you can see your data, client-side proofs settled to Ethereum let anyone verify every transaction without trusting an operator, and the off-switch stays in your hands, allowing you selectively share information.
  • Canton: Participant nodes read your data in plaintext, no outside party can verify the global ledger, and your off-switch sits with those nodes rather than with you, since disclosure depends on them staying honest.
  • Starknet: No operator ever sees your plaintext because proofs are generated client-side, and those proofs verify the rules, but your off-switch is a standing viewing key that a designated auditor can use to decrypt and trace your entire history on request.
  • Tempo: The zone operator sees every transaction in plaintext, mainnet validity proofs let anyone verify the zone ran correctly, and the operator holds the off-switch, so you are private from the public but not from the operator.
  • zkSync: The operator reads every transaction in plaintext while a validity proof on Ethereum proves it cannot forge state, and the operator holds the off-switch over who sees what, giving you privacy from the outside world but not from the operator.

The Comparison In One View

Comparison chart of privacy on Aztec, Canton, Starknet, Tempo, and zkSync

Comparing your privacy off-switch 

Each of these networks offers privacy with selective disclosure, but each rests on a different network design with its own tradeoffs. We have ordered them by who holds your privacy off-switch, starting with designs where a third party controls access to your data and ending with designs where that control stays with you. At the top, the switch sits behind a policy promise and an honest operator, and further down it is replaced by proofs that the user generates and controls.

Canton

Canton keeps data private by controlling viewing permissions for the various actors on its network. A transaction splits into per-participant views, so each party receives only the sub-transactions that name it, and the parts it is not entitled to never reach it. The sequencer and mediator move those views without reading them, which is real privacy against those roles.

However, the data is still read in plaintext by the participant nodes that host the relevant parties, and in the common regulated-asset pattern where the issuer is a signatory on its own token, the issuer's node sees every transfer. The harder gap is verification, because no third party can reconstruct the global ledger, so correctness rests on the confirming nodes staying honest and their keys staying safe. In practice the off-switch sits with those nodes rather than with you, since you cannot see when your data is read and cannot stop it.

Tempo

Tempo is designed for payments and uses validity proofs to verify that each zone is executing correctly, while still giving the zone operator full plaintext visibility into every transaction within that zone. Privacy comes from Tempo Zones, which are parallel execution environments connected to the Tempo mainnet.

By design, the zone operator has visibility into all transactions within the zone, while users see only their own and the public sees only a proof that the zone is valid. Token issuers set compliance controls, allowlists, blocklists, and freezes, enforced across zones. The mainnet checks each zone's validity, so execution is verified, while the operator still reads every transaction in plaintext and holds the off-switch over what is revealed. Your privacy is from the public, not from the operator.

zkSync Prividium

zkSync Prividium adds the verifiability piece that Canton lacks. Every batch produces a validity proof settled to Ethereum, so a compromised operator cannot forge state or mint tokens from nothing without also forging a proof, which it cannot do. The tradeoff is that the operator processes every transaction in plaintext and decides who sees what, which means the off-switch stays with the operator and your privacy is from the outside world rather than from the operator itself.

This tradeoff has legitimate uses in high-trust institutional environments. If Bank of America, JPMorgan, and Wells Fargo are transacting on a shared network, a zone where BofA's infrastructure processes BofA-originated transactions satisfies internal control requirements while still delivering genuine ZK privacy from the other banks and the rest of the world. Where this model breaks down is in lower-trust environments where giving an operator full plaintext access and the switch that comes with it holds back product design possibilities. 

Starknet STRK20

Starknet's STRK20 breaks from relying on an operator for privacy. It shields ERC-20 balances and transfers in a privacy pool, and every private transaction carries a zero-knowledge proof generated client-side, so no operator sees your plaintext in order to build it.

Disclosure is where STRK20 diverges from Aztec. To join the Starknet Privacy Pool, you register an encrypted viewing key onchain, and it sits there for the life of your participation. On a regulatory request, a designated auditing entity can decrypt that key and trace your complete transaction history, forwards and backwards. StarkWare calls this ‘not a backdoor’ but a carefully scoped access mechanism, and the safeguard is a policy promise that the auditor decrypts only when required. The privacy is cryptographic, but the off-switch is a standing key that someone else holds and can flip whether or not you are watching.

Aztec

On Aztec your private state lives as encrypted private data that only you can decrypt. The contract developer can choose what state is public and what is private, and whether your encrypted private data is emitted onchain as a private log or shared off-chain instead.

Your transactions get proven client-side on your own device, so no sequencer or operator sees your unencrypted private data. Those proofs settle to Ethereum, which gives the same integrity anchor marketed by Prividium, with every transaction verified and no forged state, but without a single operator who reads your data. The base protocol decentralizes sequencing, proving, and governance, so there is no operator to choose and trust in the first place.

Disclosure is your choice too: you decide who learns your private data, and whether they learn it in encrypted or decrypted form. To grant discovery without readability, you share an app-specific tagging secret that lets an auditor find your data in encrypted form without being able to decrypt and read it. This is enough to prove things calculated from that data, such as a tax basis or a profit and loss figure. Granting permission to actually read the data works differently. There's no per-contract read key you can hand out, because decryption uses your master viewing key, which would unlock all your data across every contract. So instead of sharing a key, you share the data itself, plus a proof that your plaintext is what encrypts to the on-chain ciphertext.

Aztec has true selective disclosure in that you can selectively share it, and nothing else you don’t need to. This is app specific, meaning that private data discoverability access on one app does not grant access on another. Most importantly, the off-switch stays in your hands, and you never need to trust the network to handle access to any of your private data and activity.

This is not just conceptual: here is a working proof-of-concept of this model on Aztec. PrivPNL takes you from private DEX trades through a tagging-key disclosure to a browser-generated ZK proof of your PnL. The auditor verifies a proof while the prover only has to reveal the amount they owe, and your portfolio stays private.

Users need to hold their own off-switch, not a promise to look away

Canton keeps the switch with the participant nodes that read your data in plaintext, so disclosure rests on those nodes staying honest rather than on anything you control. Tempo similarly gives the off-switch to a zone-based node operator, but allows you to verify the correctness of transactions using validity proofs. Prividium hardens that promise with a proof settled to Ethereum, a real improvement, but the operator still reads every transaction and still decides who sees what. This can work well for large institutions, but small to medium sized enterprises are left with the same privacy as their current banks unless they run their own Prividium nodes. STRK20 moves the switch into a standing viewing key and asks you to trust that a designated auditor reaches for it only when needed. In each of these models the real question is not whether your privacy can be switched off, but who gets to do the switching, and whether you would even know it happened.

Aztec takes the operator and the standing key out of the question entirely. You keep the data, you generate the proof, and you disclose the result, one fact at a time and only when you choose to. The off-switch never leaves your hands, and no operator, auditor, or node can reach it on your behalf. This is one of the benefits of a network that offers fully programmable, privacy-preserving smart contracts that put you in control. 

Selective disclosure is how privacy survives contact with a regulator, and the model you pick decides who can open your history when you are not looking. On Aztec, that answer is no one but you.

Let's Build

Dive into the technical details: Try a live demo of selective disclosure on Aztec and read the technical article on how it was built. 

Integrate with Aztec: Reach out if you are interested in integrating privacy into your project.

Aztec Network
Aztec Network
26 May
xx min read

The Aztec Stack

Aztec is built on one idea: smart contracts on Ethereum where developers choose what is public and what is private. That doesn't just mean shielded transactions. It means who acts (identity), what they transact (state), and how they execute (computation) can all be private. Aztec makes end-to-end privacy possible; even the contracts themselves can be private.

But privacy also has to be practical. Aztec integrates private and public execution in the same contract, so apps can seamlessly weave together private and public state. Every account is a smart contract, letting users grant granular, revocable access for selective disclosure, which is useful for compliance, tax reporting, or agent permissions.

Finally, Aztec is a decentralized L2, with 3,500+ sequencers participating in the network today. That permissionlessness is what makes Aztec a credible foundation for a global privacy layer.

In this article we’re going to explore the Aztec stack and how we make programmable privacy a reality. We’ll answer questions like ‘what can you do on Aztec?’, ‘how does it all work?’, and ‘what are the core layers of the system that makes it all possible?’

TL;DR

The four layers of the Aztec stack, all live today on the Alpha network

  1. Noir: a programming language for writing private programs with simple, familiar syntax. 
  1. Aztec smart contracts: written in Noir using the Aztec.nr framework, allowing you to easily write smart contracts with both public and private state. 
  1. Aztec Network: a fully decentralized, privacy-preserving Ethereum L2 for building useful applications. Private state uses a UTXO model, public state uses an account-based model like Ethereum. 
  1. Ethereum: L2 txn rollup proofs are stored on Ethereum, inheriting strong economic security. 

Layer 1: Noir, the Universal Language of ZK 

Aztec smart contracts are written in Noir, a programming language with Rust-like syntax optimized for writing private programs. Noir is an open-source project developed by Aztec and is now the industry-leading language for writing private apps using zero-knowledge proofs. Let’s dive into what Noir is, and why we use it as the building block for writing smart contracts. 

Writing zk programs is extremely difficult without a background in cryptography. When developing Noir, our first goal was to create a highly optimized and easy-to-write zk Domain Specific Language (zkDSL) where developers don’t need to know any of the underlying mathematics. As a result, Noir handles all the cryptographic complexities, and will automatically convert your code into fancy zk circuits. 

Noir under the hood
Noir under the hood

Noir compiles down to the Abstract Circuit Intermediate Representation (ACIR), an adaptable intermediary language that makes it easy to plug in a variety of popular proving backends. These proving backends, such as Aztec’s Barretenberg proving system, take the compiled zero-knowledge circuits and generate proofs attesting to the validity of the program’s execution, all without revealing any private inputs. From authorization systems that keep a password on the user's device, to complex onchain state channels with recursive proofs to verify offchain state; Noir and a proving backend handle everything from compilation to cryptography for you. 

In addition to simplifying the developer experience, we also wanted to make it intuitive to specify which elements you want to keep private and which you want to make public. With Noir, privacy is baked in as a default, so all variables and functions are automatically kept completely private, and executed on the user’s device. 

If you want to make any part of your code public, you can do so by simply adding a pub attribute. 

Using public and private inputs together
Using public and private inputs together

Noir on its own is great for writing programs that need to execute stateless functions, such as proving that you reside in a specific country based on passport data, or that you hold a certain number of tokens without revealing how many. Projects are already starting to build with Noir outside of Aztec on Base, Scroll, Starknet, and other chains. However, if you are looking to write privacy-preserving apps that store private state data onchain, it’s helpful to utilize a smart contract library that deliberately handles those complexities for you. That’s exactly what we’ve built at Aztec and what we’ll explore in the next section. 

Layer 2: Smart Contracts 

Aztec smart contracts leverage Noir to create apps with onchain private and public state. This section covers how smart contracts work on Aztec and how you deploy and interact with your contracts. 

An Aztec smart contract is a set of public and private functions written in Noir, deployed on the Aztec Network. They are written using the Aztec.nr framework which handles all the cryptography under the hood for managing private and public state and interacting with other contracts on the network. 

To build useful applications, developers need to be able to incorporate both private and public components into their contracts. For example, an onchain voting contract might want to keep the information of the voter private and prevent someone from voting twice, but publicly display how many votes have been cast, and the outcome. 

Because contracts are written in Noir, this functionality is as easy as adding a ‘private’ annotation above your function. The following function will be executed privately on the user device, allowing a user to cast a vote without revealing their address: 

The output of this private, local execution will be sent to the network, where the correctness of execution is verified and public function calls are executed. The following function is designed to be executed publicly, adding a vote to the total tally without revealing where it came from. 

To seamlessly weave together private and public components that can easily interact with onchain state, Aztec smart contracts utilize the Aztec.nr framework to execute private functions on the user’s device and bundle the proofs for these transactions together with the public functions that will be executed by the Aztec Virtual Machine (AVM). 

This framework adds the functionality needed to build onchain, privacy-preserving apps, including defining contracts, accessing private or public context, and interacting with the Aztec Network. Similar to how a vanilla Noir program would compile down into zk circuits, Aztec smart contracts are compiled into zk circuits for private functions or AVM bytecode for public functions, and stored in the Aztec contract tree. 

Aztec accounts are also written as smart contracts, implementing what is known as account abstraction. Account abstraction allows application developers to create programmable accounts to dramatically improve user experience, including social recovery, sponsored transactions, and multi-factor authentication. It also makes compliance practical, allowing for granular access controls on accounts. 

Layer 3: The Aztec Network

The Aztec Network is the only decentralized L2 on Ethereum. There are currently over 3,500 sequencers running the alpha network. View the live block explorer for the alpha network. 

In order for a network to fully protect users and their data, it must guarantee three levels of privacy: 

  • Private data: input and output values are hidden
  • Private identity: addresses are hidden 
  • Private compute: contract functions are hidden 

When you write  Aztec smart contracts, everything listed  above is taken care of for you. As discussed in the previous two sections, you can easily opt into privacy protections at a granular level by weaving together public and private functions. 

To understand how all of these components fit together, let’s examine how a transaction is executed on the Aztec Network. 

When a user interacts with your application, private functions are executed client-side on the user’s device: a phone, a personal computer, etc. This happens in a private execution environment (PXE) that is able to create highly-efficient zk proofs even on browsers and mobile devices. Any private state updates are added to the state of the network in an append-only database (UTXO tree). Because the proof is generated client-side, no information can be leaked about the inputs, outputs, accounts, or even the functions that were executed.

On the other hand, public transactions are bundled together with the private client-side proofs and sent off to the Aztec Network, powered by a decentralized network of independent community-run sequencers. Sequencers check the validity of private execution proofs, execute any public functions and update the public state, propose blocks, and publish state updates (“diffs”) to Ethereum L1. Sequencers also coordinate with a decentralized network of provers who compute the final proof for every Aztec “epoch” - defined as a contiguous sequence of 32 L2 blocks - and publish it to Ethereum. Any public functions executed by sequencers update an account-based database similar to Ethereum. 

Sequencer and prover roles are fully permissionless. Anyone can spin up the required hardware and join the sequencer set or run provers and start bidding to produce proofs of Aztec epochs. 

Conclusion

Aztec delivers on a simple but powerful idea: smart contracts on Ethereum where you choose what's public and what's private across identity, data, and compute. The four layers we've walked through are what make that possible.

Noir gives developers a Rust-like language for writing zero-knowledge programs without a cryptography background, with privacy as the default. Aztec smart contracts build on Noir through the Aztec.nr framework, letting you weave private and public functions into a single contract and use account abstraction to unlock granular access controls for compliance, tax reporting, and selective disclosure. The Aztec Network is the only decentralized L2 on Ethereum, with over 3,500 sequencers powering end-to-end programmable privacy across data, identity, and compute. And it all settles to Ethereum, inheriting L1's economic security.

The result is the first practical platform for privacy on Ethereum, and a credible candidate to become the global settlement layer of the future.

Now it's your turn to build. Head to docs.aztec.network to ship your first privacy-preserving app.

Follow Aztec on X for updates on the current state of the network.