Aztec Network
Mar 11th, 2024
## min read

Client-side Proof Generation

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.

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Written by
Lisa A.
Edited by

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.

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Aztec Network
Aztec Network
7 Aug
xx min read

Alpha V5 Proving System Vulnerability

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.

Community
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
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
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 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.