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Omer Goldberg
Omer Goldberg

Benqi veQI Economic Analysis

Cover Image for Benqi veQI Economic Analysis
  1. Overview
  2. Objective
  3. Assumptions
  4. Theoritical Efficient Quantity of Staked QI
  5. Simulated Scenarios
    1. Defining Risk Appetite
    2. Price Impact
  6. Simulation Flow
  7. Results
    1. 1. Current Market Conditions (9/19/22) - Exchange Rate 1680, Total Benqi staked AVAX is 5M
  8. 2. Exchange Rate 1550, 40M Benqi staked AVAX
  9. 3. Exchange Rate 1000, 40m Benqi staked AVAX
  10. Edge Cases Drill Down
    1. 1. Minimum Risk Premium is 0% and Price Impact is 0
    2. 2. Minimum Risk Premium is 0% and Price Impact is 1%
  11. 3. Minimum Risk Premium is 50% and Price Impact is 0%
  12. 4. Minimum Risk Premium is 50% and Price Impact is 1%
  13. Conclusions
  14. About Chaos Labs

Overview

Popular on blockchains that utilize Proof of Stake consensus protocols, Liquid Staking refers to an innovative approach to staking in which a user can stake their tokens without losing access to them. The tokens have been staked (often by delegating this process to a third party), but they’re still available as liquidity, hence the name ‘Liquid Staking’.

As Liquid Staking becomes a more mature and important approach to securing blockchains, it becomes necessary to quantify, analyze, and answer certain questions. In particular, we want to know whether veQI is beneficial for both validators and BENQI tokenholders and, if so, what is the optimal model and parameterization for achieving the maximum utilization veQI?

To address these questions we must first understand the potential validator's motivations. What are the primary incentives for validators, and what is the upper bound on the upside they can capture? What are the economic risks and deterring factors for potential validators which must be weighed against this upside? When is Qi staking profitable enough for validators to be incentivized to participate? Can we predict veQI staking strategies and how it impacts the efficiency of Liquid Staking as a whole?

Getting clarity on these complex technical matters is our purpose in this document.

Objective

Benqi’s goal is to create a Liquid Staking model that is beneficial to validators while aligning their incentives to that of the QI community.

The simplified QI staking plan is to delegate the 30% of staked AVAX to validators according to their proportional holdings of veQi (proportional holdings are also referred to as their ‘weight’). veQi is emitted along similar lines as the PTP - vePTP model and veQI validators are able to set delegation fees from 2% to 5%.

1 staked PTP generates 0.014 vePTP every hour. The maximum vePTP held from a deposit is 100 times the PTP staked. In other words, it takes about 10 months to reach the vePTP cap. You can always stake more PTP to earn more vePTP, and you can withdraw your staked PTP at any time, but your accumulated vePTP will drop to 0 as soon as you unstake any amount.

For our analysis, the anchoring data we used was:

  • AVAX validators make ~8% APR from their staked AVAX
  • The circulating supply of QI is 2.9B
  • The price of 1AVAX = 1680QI
  • The total amount of sAVAX in Benqi is approximately 5M

Assumptions

Our model makes the following assumptions:

  1. All validators are rational.
  2. There is an unlimited supply of Qi at the current price.
  3. Validators consider the risk of holding QI equal to the risk of holding AVAX.
  4. Qi will not be un-staked if the validator continues validating, and we assume all of them do. Under this assumption, over a period of time greater than a year $veQi(user) ~= stakedQi(user)$

Theoritical Efficient Quantity of Staked QI

What follows from these robust assumptions?

First, the maximum extractable value to the protocol from staked QI is 5% of overall AVAX rewards. The value of the AVAX staked by validators can therefore be expressed

From this (and assumption #3 above) it follows that the total value of QI which grants the right to receive 1.5M AVAX in delegations will be 75K AVAX (around $1.425M at current price levels).

Based on assumption #2, there is an unlimited supply of QI at the current price, so

If all validators are rational (assumption #1), we should expect that approximately 123,300,000QI will be purchased and staked. Given that the circulating supply of QI is about 2.69B, the percent locked QI will be:

Simulated Scenarios

In a real-world scenario, we assume validator behavior will tend to converge to rational behavior because the competition amongst a large number of actors will tend to drive out market inefficiencies.

We have simulated different scenarios which test various levels of risk appetite and price impact. Each scenario was tested over 10 delegation epochs, and in each epoch, we simulated a group of validators assessing the profitability of buying QI based on two varying parameters:

  • their risk appetite, i.e. the risk premium they require in order to hold QI over AVAX
  • the price impact of buying QI.

Defining Risk Appetite

The risk appetite of validators is measured by their willingness to buy QI instead of holding AVAX, which would grant them an equivalent value in rewards. On the whole, we anticipate risk appetite among validators will increase over time as they grow to trust QI and as they see the first validators acquiring (and staking) QI.

We simulated a range of risk appetite scenarios by translating it into a price discount they require in order to hold QI instead of AVAX. In each simulation, the initial price discount validators expect in order to hold QI over AVAX is 90%. As expected, over the course of the simulation risk the price discount decreases to the range of 0%-50%, indicating growth in risk appetite.

Price Impact

Price Impact is hard to predict as there are other stakeholders already holding QI. We measure this by simulating a range of price impact scenarios. For Every 1M QI bought by validators, we estimate a price increase by D, ranging between 0% and 1%

Simulation Flow

We approached simulation by computing potential validators (using either real or synthesized validator data), as follows.

  • For each epoch in [0,T-1], grant existing users new $veQI, with one staked QI generating $e$ units of $veQI every round.
  • Delegate available $AVAX to users according to their weight (i.e. their share of $veQI), up to their max capacity. Delegations only last a single epoch, so terminate any made 1 epoch prior to the current round.
  • Then, estimate new staking in the current epoch.

    1. Staking QI is only profitable if :
  • If this condition holds, calculate the amount of QI required to buy staked AVAX delegation,

Then, randomly select a set of validators such as their total capacity < staked AVAX, and have them buy and stake a new QI amount. With that done calculate the new exchange rate the new risk premium.

Results

We executed 100 simulations for every set of parameters, randomizing the validator staking order for each simulation. Relevant validator data (eligibility, capacities, etc.) is based on a snapshot of current data from the network (taken on 09/19/22). Each simulation is run for 20 epochs, where each epoch is 14 days. The risk premium is increased every epoch and the QI market price increases for every 1M QI bought.

Below is the mean result for each simulation configuration:

1. Current Market Conditions (9/19/22) - Exchange Rate 1680, Total Benqi staked AVAX is 5M

Each point in the map represents the total amount of Qi staked in simulation under a given configuration of price impact and risk premium. Assuming 0% price impact (assumption #2) and 100% risk appetite (assumption #3), we get an upper bound of 116M on the amount of staked Qi (bottom left corner), which accords with the upper bound calculated above.

Intuitively, we would expect the upper bound to be reduced linearly by introducing a risk premium (Y axis). A higher price impact reduces the amount of staked QI tokens, but the value of staked QI in terms of AVAX should remain the same along the X axis.

Total Staked QI[M]

Each point in the map represents the total amount of Qi staked in simulation under a configuration of price impact and risk premium. Assuming 0% price impact (assumption #2) and 100% Risk appetite (assumption #3), we get the upper bound on the amount of staked Qi of 123M (bottom left corner), equating to the bound calculated above. Intuitively, we would expect the upper bound to be reduced linearly by introducing a risk premium (Y axis). A higher price impact reduces the amount of staked QI tokens, however value of staked QI in terms of AVAX should remain the same along the X axis.

Final AVAX: QI Exchange Rate

We see the significance of price impact on the amount of QI that can be locked. It gets less profitable to stake additional QI as the token price increases. However, that is a desired outcome of the protocol, as it creates a high dependency between AVAX and QI prices.

2. Exchange Rate 1550, 40M Benqi staked AVAX

We ran a separate scenario with increased AVAX staked in Benqi, representing approximately 15% of AVAX circulating supply.


3. Exchange Rate 1000, 40m Benqi staked AVAX

Edge Cases Drill Down

1. Minimum Risk Premium is 0% and Price Impact is 0

In the best-case scenario (bottom left corner of heat map), a total of 116M $QI were staked by validators, at a total cost of 75K AVAX. Below are the results per each validator:

bls_results_risk_100_price_0

Each plot in the figure below represents a single validator. As risk premium decreases rapidly, we see the entire amount of QI staked in the first 2 epochs. Over 20 epochs we see the weights stabilize as veQI(user) ~= stakedQi(user), which shows the validity of assumption #4.

Weights of validators (veQI relative amount owned by validator) over the course of the simulation.

2. Minimum Risk Premium is 0% and Price Impact is 1%

n this scenario we introduce the effect of 1% price impact (bottom right corner of heat map) - for every 1M QI bought, the AVAX-QI exchange rate decreased by 1%. a total of 63M $QI were staked by validators, at a total cost of 75K AVAX. Below are the results per each validator:

bls_results_risk_100_price_1

Weights of validators (veQI relative amount owned by validator) over the course of the simulation.

The weight distribution remains similar, as risk appetite grows at the same rate as scenario 1, and assumption #4 still holds. We can see the QI

exchange rate goes down to ~830 after ~60M Qi is bought.

Price Trajectory - Amount of 1 AVAX: QI, change over amount of QI bought for staking.

3. Minimum Risk Premium is 50% and Price Impact is 0%

In this scenario, we assume validators would demand a minimum of 50% risk premium over the entire course of the simulation (upper left corner of the heat map). This effectively reduces the price a given validator would be willing to pay for Benqi-staked AVAX by 50%. A total of 59M $QI were staked by validators, at a total cost of 38K AVAX. Below are the results per each validator:

bls_results_risk_50_price_0

4. Minimum Risk Premium is 50% and Price Impact is 1%

In terms of total QI locked (the upper right corner of the heat map), this scenario represents the worst case. The combined effect of the high minimum risk premium and the high price impact lead to a total of only 40M $QI staked by validators, at a total cost of 30K AVAX. Below are the results per each validator:

bls_results_risk_50_price_1

Weights of validators (veQI relative amount owned by validator) over the course of the simulation.

Price Trajectory - Amount of QI: 1 AVAX, change over amount of QI bought for staking.

Conclusions

These simulations can tell us many things about the incentives and market dynamics of this ecosystem. First, we see that increasing staked AVAX in BENQI should linearly increase the amount of QI staked as veQI in the protocol. Second, a high-risk premium actually increases validators’ profit, as validators receive the same amount of delegation but are willing to pay less for it. Third, we expect the actions of rational market participants to eventually drive the minimum risk premium demand to 0%--but bear in mind the difficulty of predicting the rate of risk appetite growth and the different risk profiles of validators if assumption #1 doesn’t hold. And finally, as long as assumption #4 holds price impact reduces the amount of Qi tokens locked, but does not affect the value locked in terms of AVAX.

Validators who are early to stake can realize outsized ROI compared to those who stake later, due to the yield of accumulated rewards. We are building an associated BENQI Liquid Staking ROI Calculator to better measure this opportunity (similar to the Rewards Calculator built for dYdX).

If you are an AVAX validator and want to learn more, please contact us at benqi@chaoslabs.xyz.

About Chaos Labs

Chaos Labs is a software company building a simulation platform to allow teams to efficiently test protocols and understand how they will react to adversarial market environments. The backbone of our technology is a cloud-based, agent- and scenario-based simulation platform that allows users to orchestrate blockchain state, test new features, and optimize risk parameter selection.

Our technology allows users to:

  • Orchestrate protocol/blockchain state
  • Generate wallets with behavioral attributes
  • Test protocol performance in chaotic market conditions
  • Optimize risk parameters

Our mission is to secure and optimize protocols through verifiable agent- and scenario-based simulations.

The Chaos Labs simulation platform is built to emulate a production environment. Each simulation runs on a mainnet fork with the chain's current state so that your simulations include up-to-date account balances and the latest contracts and code deployed across DeFi. You cannot look at your protocol in a silo when you're testing adversarial environments. You must ensure you understand how external factors such as cascading liquidations, oracle failures, variable gas fees, liquidity crises, and more will impact your protocol in various situations.

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Omer Goldberg
Cover Image for Introducing the GHO Risk Monitoring Dashboard by Chaos Labs

Introducing the GHO Risk Monitoring Dashboard by Chaos Labs

Chaos Labs unveils a new version of the Aave v3 Collateral At Risk Dashboard monitoring the GHO deployment on the Goerli testnet in preparation for mainnet launch.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Raises $20M in Seed Funding to Automate On-Chain Risk Optimization

Chaos Labs Raises $20M in Seed Funding to Automate On-Chain Risk Optimization

Chaos Labs raises Seed funding led by Galaxy and Paypal Ventures to automate on-chain risk optimization.

Omer Goldberg
Omer Goldberg
Cover Image for AAVE v3 Collateral At Risk Dashboard Expands Deployments Support to Ethereum v3

AAVE v3 Collateral At Risk Dashboard Expands Deployments Support to Ethereum v3

Following the successful launch of the AAVE v3 Collateral At Risk Dashboard, we're proud to announce expanded support for Ethereum v3.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Unveils Parameter Recommendation Platform.

Chaos Labs Unveils Parameter Recommendation Platform.

After becoming full-time contributors to the Aave protocol in 2022, Chaos Labs has been working on all fronts to deliver tools that will increase the community’s understanding of Aave and its potential. We’re proud to publish V0 of the Chaos Labs parameter recommendation platform to the community!

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Selected by Uniswap Foundation for TWAP Oracle Research Grant

Chaos Labs Selected by Uniswap Foundation for TWAP Oracle Research Grant

Preceded by earlier V3 TWAP oracle research, the Uniswap Foundation announces a Chaos Labs grant.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs & Hathor Nodes launch platform to optimize Osmosis incentive distribution

Chaos Labs & Hathor Nodes launch platform to optimize Osmosis incentive distribution

Funded by the Osmosis Grants Program, the pair launches an open-sourced incentives model and community dashboards.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs receives a Uniswap Foundation grant for LP strategies for V3

Chaos Labs receives a Uniswap Foundation grant for LP strategies for V3

Chaos Labs has been awarded a grant from the Uniswap Foundation to test and simulate sophisticated LP strategies.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs helps navigate DeFi volatility with an expanded Aave V2 risk partnership

Chaos Labs helps navigate DeFi volatility with an expanded Aave V2 risk partnership

Chaos Labs announces further collaboration with Aave to include Aave V2 risk coverage.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Osmosis Liquidity Incentives Portal Update

Chaos Labs Osmosis Liquidity Incentives Portal Update

An update on the Osmosis Liquidity Incentives Portal collaboration with Hathor Nodes.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches Benqi Risk Dashboard

Chaos Labs Launches Benqi Risk Dashboard

Chaos Labs is launching the Benqi Risk Dashboard, utilizing real-time user metrics to understand the value at risk across volatile markets as well as yield earned and paid over time.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Asset Protection Tool

Chaos Labs Asset Protection Tool

Chaos is unveiling a new tool to measure price manipulation risk and protect against it. Introducing the Chaos Labs Asset Protection Tool

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Joins AAVE as Full-Time Contributor

Chaos Labs Joins AAVE as Full-Time Contributor

After a successful governance vote, Chaos Labs is joining Aave as a full-time contributor to focus on risk management and parameter recommendations for all Aave v3 markets.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Osmosis Grant

Chaos Labs Receives Osmosis Grant

Chaos Labs has received a grant from the Osmosis Grants Program and will partner with Hathor Nodes on optimizing the Osmosis incentives program.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs <> Benqi veQI Calculator

Chaos Labs <> Benqi veQI Calculator

Chaos Labs, a cloud security platform for DeFi applications, announces the launch of the Benqi veQI calculator.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Auction Price Curve & Keeper Gas Strategies (Pt. 4)

Maker Simulation Series: Auction Price Curve & Keeper Gas Strategies (Pt. 4)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate how Keepers with competing gas strategies impact the Auction Price Curve for liquidations.

Omer Goldberg
Omer Goldberg
Cover Image for Benqi veQI Economic Analysis

Benqi veQI Economic Analysis

Diving deep into Benqi's veQI tokenomics and utility.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Peg Stability Module (Pt. 3)

Maker Simulation Series: Peg Stability Module (Pt. 3)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model PSM simulations.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs launches AAVE v3 Risk Bot

Chaos Labs launches AAVE v3 Risk Bot

The AAVE v3 Risk bot will provide monitoring, notifications and daily summaries for risk related activity across all v3 deployments.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Flapper Surplus Dai Auctions (Pt. 2)

Maker Simulation Series: Flapper Surplus Dai Auctions (Pt. 2)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate Flapper Surplus DAI auctions.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches AAVE v3 Risk Application

Chaos Labs Launches AAVE v3 Risk Application

Chaos Labs, a cloud security platform for DeFi applications, has launched an AAVE v3 collateral at risk and real-time user metrics dashboard.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Flipper Black Thursday (Pt. 1)

Maker Simulation Series: Flipper Black Thursday (Pt. 1)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate Flip Auctions, liquidations and auctions.

Omer Goldberg
Omer Goldberg
Cover Image for AAVE Simulation Series: stETH:ETH Depeg (Pt. 0)

AAVE Simulation Series: stETH:ETH Depeg (Pt. 0)

A simulation series focused on economic security for the AAVE protocol. Let's examine the effect of a stETH:ETH depeg.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Introduction (Pt. 0)

Maker Simulation Series: Introduction (Pt. 0)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate liquidations and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Dives Deep Into AAVE v3 Data Validity

Chaos Labs Dives Deep Into AAVE v3 Data Validity

Chaos Labs, a cloud security platform for DeFi applications, has discovered

Ron Lev
Ron Lev
Cover Image for Chaos Labs Collaborates with Benqi For Liquid Staking Analytics

Chaos Labs Collaborates with Benqi For Liquid Staking Analytics

Chaos Labs, a cloud security platform for DeFi applications, announces a partnership with Benqi to support Liquid Staking on the Avalanche network.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives AAVE Grant

Chaos Labs Receives AAVE Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded an AAVE Grant to build a collateral at risk and real-time user metrics dashboard.

Omer Goldberg
Omer Goldberg
Cover Image for Pushing Economic Security Boundaries with MakerDAO Pt. 2

Pushing Economic Security Boundaries with MakerDAO Pt. 2

Chaos Labs, a cloud security and testing platform for smart contract applications, has created a cloud platform for Maker to test their liquidation and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Source Uniswap v3 TWAP Hardhat Plugin

Chaos Labs Open Source Uniswap v3 TWAP Hardhat Plugin

Chaos Labs, a cloud security platform for DeFi applications, has open source a utility package for interfacing with Uniswap v3.

Omer Goldberg
Omer Goldberg
Cover Image for Uniswap V3 TWAP Oracle Deep Dive - Pt. 2

Uniswap V3 TWAP Oracle Deep Dive - Pt. 2

An in depth look at Uniswap v3 TWAP architecture and usage in development.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Maker Liquidity Rewards Distribution Report

dYdX Maker Liquidity Rewards Distribution Report

Chaos Labs releases the dYdX Market Maker Liquidity Rewards Distribution Report.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Chainlink Grant to build Terra Oracle Infrastructure

Chaos Labs Receives Chainlink Grant to build Terra Oracle Infrastructure

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Chainlink Grant to build tooling and infrastructure for Terra Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs releases the dYdX Perpetual Funding Rate App

Chaos Labs releases the dYdX Perpetual Funding Rate App

Chaos Labs releases the dYdX Perpetual Funding Rate application for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Sources Chainlink Price Feed NPM Module

Chaos Labs Open Sources Chainlink Price Feed NPM Module

Chaos Labs, a cloud security platform for DeFi applications, has open source a utility package for interfacing with Chainlink price feeds.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Sources dYdX Trading CLI

Chaos Labs Open Sources dYdX Trading CLI

Chaos Labs, a cloud security platform for DeFi applications, has open sourced a trading tool for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Pushing Economic Security Boundaries with MakerDAO

Pushing Economic Security Boundaries with MakerDAO

Chaos Labs, a cloud security and testing platform for smart contract applications, has created a cloud platform for Maker to test their liquidation and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Uniswap v3 TWAP Oracle Tooling and Deep Dive Pt. 1

Uniswap v3 TWAP Oracle Tooling and Deep Dive Pt. 1

Chaos Labs, a cloud security platform for DeFi applications, has released open source tooling for developing with Uniswap v3 TWAP Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives dYdX Grant

Chaos Labs Receives dYdX Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a dYdX Grant to build analytics and tooling for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Uniswap Grant

Chaos Labs Receives Uniswap Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Uniswap Grant to build tooling for Uniswap v3 TWAP Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Adds Chainlink Oracle Cloud Integrations

Chaos Labs Adds Chainlink Oracle Cloud Integrations

Chaos Labs receives grant to enhance Chainlink Oracle Cloud Testing Environment.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs joins Maker SES

Chaos Labs joins Maker SES

Chaos Labs, a cloud security and testing platform for smart contract applications, has recently joined the SES incubation program.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Chainlink Grant

Chaos Labs Receives Chainlink Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Chainlink Grant.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Mission Statement

Chaos Labs Mission Statement

Chaos Labs is a cloud security and testing platform for smart contract applications. Mission statement coming soon 🎉 🥳

Omer Goldberg
Omer Goldberg