Custom GMX Fork Development for Perpetual DEX
We develop GMX forks for perpetual DEXs, adapting the architecture to specific requirements. GMX is not just a protocol—it's a proven architecture: the GLP pool as the counterparty, zero-price-impact order execution (up to a certain threshold), and oracle-based pricing instead of an order book. Forking GMX is not "copying contracts"; it's understanding the risk management system between LPs and traders and adapting it to your goals.
Our blockchain development experience exceeds 10 years, and we have successfully deployed 5+ GMX forks on L2 networks, maintaining 99.9% uptime of the keeper network. Order a GMX fork development from us—we will audit your requirements and propose the optimal architectural solution.
How Does GLP Manage Risk?
In GMX v1, liquidity providers deposit assets into the GLP vault—a multi-asset pool acting as the counterparty for traders. When a trader opens a long on ETH, they borrow ETH from the GLP (via the reserved amount mechanic). If the price rises, GLP loses; the trader wins—and vice versa. GLP profitability correlates with the percentage of losing traders. The balance is maintained by fees and the size of open positions.
When forking, you must explicitly decide: which assets enter the pool? What is the maximum allocation per asset (in GMX: ETH ~35%, BTC ~25%, stablecoins ~40%)? How is rebalancing managed via dynamic mint/redeem fees? Incorrect allocation balance leads to pool insolvency risk under directional market pressure.
Why Is Protection Against Oracle Manipulation Important?
GMX uses Chainlink + Binance/Coinbase price aggregation with a bid/ask spread. The spread between them is the primary defense mechanism. A position is opened at ask and closed at bid. In GMX v2, a synthetic market through GLV vault and a keeper system eliminating MEV was introduced.
If you use only Chainlink without a custom price aggregator, a latency of 1–3 blocks during extreme volatility creates a window for price arbitrage. Several GMX v1 forks have lost funds due to this—traders opened positions knowing the next oracle price. We implement multi-oracle aggregation with dynamic spread and deviation monitoring.
What Risks Does a GMX Fork Carry?
Main risks: oracle arbitrage during volatility, bad debt from non-liquidated positions, keeper network failure, suboptimal GLP pool balance. For example, during a black swan event without ADL (Auto-Deleveraging), the pool may become insolvent. We minimize risks through redundant keepers, fuzz testing, and strict risk-management parameters.
How to Prevent Bad Debt and Liquidations?
In GMX, a position is liquidated when losses + fees exceed collateral minus liquidationFeeUsd. The problem: during extreme movements, a position can become negative collateral faster than a keeper can liquidate—resulting in bad debt. In v2, this is solved via ADL: when utilization is high, the most profitable positions are forcibly closed. A fork without ADL risks systemic insolvency during a black swan.
Fork Architecture and Key Changes
| Contract |
Role |
What We Change in the Fork |
| Vault |
Asset storage, P&L calculation |
Fees, supported tokens |
| GlpManager |
Mint/redeem GLP |
Basket composition, limits |
| PositionRouter |
Order management |
Execution fee, delay |
| OrderBook |
Limit/stop orders |
Tick size, min size |
| PriceFeed |
Oracle aggregation |
Sources, spread logic |
| RewardRouter |
Staking, APR distribution |
Emission schedule |
In GMX v1, the codebase is written in Solidity 0.6.x. We migrate to 0.8.x with explicit overflow protection, removing SafeMath and enabling built-in compiler checks.
What Is Keeper Infrastructure?
For a production fork, keeper infrastructure is required: at least 2–3 keepers with failover, monitoring of pending orders, automatic gas increase for stuck transactions. The keeper is critical infrastructure—if it fails, orders are not executed, liquidations do not occur, and the pool accumulates risk. We build keeper systems in TypeScript with viem, a Redis queue for pending orders, Prometheus metrics, and PagerDuty alerts. Execution latency must be <2 blocks from the moment an executable position appears.
Technical details of keeper architecture
The keeper monitors IncreasePositionRequest and DecreasePositionRequest events. When a new event appears, it forms a multicall with executeIncreasePosition or executeDecreasePosition. To avoid race conditions, it uses a Redis lock for each position. In case of an error (e.g., out-of-gas), it retries with increased gas price.
Comparison of GMX Versions
| Parameter |
GMX v1 |
GMX v2 |
| Liquidation |
Keeper call |
Keeper + ADL |
| Oracle |
Chainlink + aggregation |
Synthetic markets |
| Fee |
0.1% trading fee |
Dynamic |
| Pool composition |
Fixed weights |
Flexible basket |
What's Included in the Work
- Audit and documentation of smart contracts
- Setup of keeper infrastructure with monitoring
- Integration of The Graph subgraph for position history
- Frontend adaptation (TradingView, wagmi, viem)
- Team training and post-launch support
Process of Work
Analysis (1 week). Audit of target chain (Arbitrum, Avalanche, Base—GMX forks live on L2 due to gas costs), competitive analysis, tokenomics.
Design (1–2 weeks). Adaptation of contracts, storage layout, asset list, risk-management parameters (max leverage, max OI per market).
Development (6–10 weeks). Smart contracts + keeper infrastructure + subgraph + frontend.
Testing (2 weeks). Fork tests with cascade liquidation simulations, oracle latency, keeper failure. Fuzz tests for PnL and liquidation logic.
Audit. Two independent external auditors before mainnet.
Deployment and monitoring. First testnet with real keepers, then mainnet with limited positions for the first 30 days.
Timeline Estimates
A GMX v1 fork on a new EVM chain with a custom pool composition takes 2–3 months. A GMX v2 fork with a full keeper system and subgraph takes 3–4 months. Timelines include audit and phased launch. The cost is calculated individually based on integration complexity and required customization.
According to GMX documentation, the GLP pool uses a multi-asset basket with dynamic allocation.
Contact us for a consultation—we will help assess the scope of work and propose the optimal solution for your project.
DeFi Protocol Development
We design modular DeFi protocols where the math of stablecoins, liquidity, and oracles works flawlessly. Mango Markets is a stress test: the attacker manipulated the spot price through a single account, took a loan against inflated collateral, and withdrew $114 million. The oracle took the price from a single source without TWAP. Not a code bug—it was an architectural decision that became a vulnerability. Our experience shows: any DeFi protocol is a system of bets that all components, from calculations to economic incentives, are correctly aligned simultaneously.
We don't write code under the 'if it works, don't touch it' mindset. We model stress scenarios: cascading liquidations, depegs, flash loans. Only then do we build events that won't break the protocol.
Why are oracles a critical component of DeFi?
Most major DeFi hacks started with oracle manipulation. Let's break down the three layers we use in every project.
Spot price as oracle—not an option. Uniswap v2 spot price can be shifted by a flash loan in one transaction. The price at the end of the block is the only one that enters the state, and the oracle reads it. Attack scheme: borrow via flash loan → buy asset into the pool → price rises → take a loan against inflated collateral → sell asset → repay flash loan. One transaction.
TWAP as protection. Uniswap v3 observe() averages the price over a period (30 minutes). Manipulation requires maintaining the price for several blocks—this is expensive. But TWAP reacts slowly to legitimate changes, opening a window for arbitrage on liquidation during sharp movements.
Chainlink Price Feeds are an aggregation from multiple data providers with a median. Standard for lending. Problem: heartbeat 1–24 hours and deviation threshold 0.5%. If the price doesn't move, the feed may not update for a day. In volatile markets—lag.
| Oracle |
Mechanism |
Manipulation Protection |
Latency |
| Chainlink |
Median from independent providers |
High (decentralization) |
Up to 24h at 0% movement |
| Uniswap v3 TWAP |
Average price over N blocks |
High (hard to maintain) |
30 min – 1 h |
| Pyth Network |
Cross-chain low-latency |
Medium (dependent on publisher) |
Seconds |
In production, we use a two-tier check: Chainlink aggregator + Uniswap v3 TWAP as a verifier. If the discrepancy exceeds N%, the transaction is rejected and the system is paused.
How to protect a DeFi protocol from flash loan attacks?
Flash loans turn any user into an owner of unlimited capital for one transaction. Therefore, when designing contracts, we assume: everyone has access to unlimited capital. This completely changes the threat model.
Legitimate uses of flash loans are arbitrage, liquidation, and self-liquidation. But the protocol must verify that the loan is not used for manipulation: the oracle must not read the price from a pool that can be shifted in one transaction. We add checks on block.timestamp and minimum liquidity depth.
Key Components of DeFi Architecture
| Protocol Type |
Core Mechanism |
Main Risk |
| DEX (AMM) |
x*y=k or concentrated liquidity |
impermanent loss, oracle manipulation |
| Lending |
collateral ratio, liquidation |
bad debt during cascading liquidations |
| Yield aggregator |
auto-compounding strategies |
rug via strategy upgrade |
| Derivatives / Perps |
funding rate, mark price |
liquidation cascades, socialized losses |
| Liquid staking |
stETH-style rebasing |
depegging on mass unstake |
AMM: From x*y=k to Concentrated Liquidity
Uniswap v2 uses x * y = k. LP tokens are ERC-20—each pool issues its own token proportional to the share. Problem: liquidity is spread across the entire curve, most of it unused.
Uniswap v3 and ERC-721 positions: concentrated liquidity—LPs provide liquidity in a range [priceLow, priceHigh]. Capital efficiency up to 4000x for stable pairs. But ERC-721 breaks vault strategies built for ERC-20. Range management is a separate engineering challenge: a position falls out of range when the price moves, stops earning fees, and becomes single-asset. Protocols like Arrakis Finance automatically rebalance. If you build a vault on top of v3, you need your own range manager or integration with an existing one.
Slippage in v3 is calculated via sqrtPriceX96—96-bit fixed-point math. Errors on the frontend lead to discrepancies between visible and actual slippage.
Curve for pairs with close prices (stablecoin/stablecoin, stETH/ETH) uses an invariant combining constant product and constant sum. Lower slippage within the peg range. Contracts are in Vyper, code is mathematically dense, auditing is difficult.
Lending Protocols: Collateral, Liquidation, Bad Debt
LTV defines the maximum loan against collateral. Liquidation threshold is the level for liquidation. The difference is the buffer for the liquidator. Typical example: LTV 75%, liquidation threshold 80%, bonus 5%. If the price drops 20%+, the position is open for liquidation.
Cascading liquidations: many positions are liquidated simultaneously → liquidators sell collateral → price drops → next wave. LUNA/UST 2022 is a classic cascade.
If collateral devalues faster than liquidation, the protocol incurs bad debt. Aave uses a Safety Module (staked AAVE), Compound uses reserves. Without a backstop, bad debt is socialized via dilution of the supply token or netting.
Designing a liquidation system requires modeling stress scenarios: a single liquidation bot failure, high gas, collateral delisting.
Yield Farming and Incentive Mechanics
Liquidity mining distributes governance tokens to LP providers. Problem: mercenary capital—farmers come, sell tokens, leave. TVL is illusory.
Sustainable mechanics: protocol-owned liquidity (Olympus bonding), veToken (CRV locked → boost + governance), locked staking with penalty. The ve-model, if implemented incorrectly, creates governance concentration. A timelock on gauge weight changes and limits on voting power are needed.
What Our DeFi Protocol Development Includes
- Architectural documentation: contract interaction diagrams, liquidation stress tests, oracle calculations.
- Implementation in Solidity 0.8.x with OpenZeppelin 5.x (AccessControl, ReentrancyGuard, Pausable, TimelockController) and Solmate for gas-optimized base contracts.
- Foundry fork tests on real mainnet (Uniswap, Chainlink, Aave) — pre-deployment tests cover all scenarios.
- Audit: at least two independent auditors for TVL over $1M. Code4rena or Sherlock for bug bounty.
- Deployment with Gnosis Safe 3/5 multisig + timelock 48–72 hours.
- Monitoring via Tenderly (alerts, simulations), OpenZeppelin Defender (automation), Forta (on-chain threat detection).
- Post-launch support: updates, patches, upgrades via proxy.
Our Expertise and Experience
We have been developing DeFi protocols since 2020, delivering 30+ projects with a combined TVL of over $150 million. Our clients include protocols in the top 20 by TVL on Ethereum, Arbitrum, and Base. The team consists of certified Solidity developers who have completed ConsenSys Diligence audit tracks.
DeFi basic principles that we apply in practice.
Timelines
- DEX with AMM (Uniswap v2 fork): 6–10 weeks
- Lending protocol (Aave-style, single collateral): 3–5 months
- Yield aggregator with multiple strategies: 2–4 months
- Full-fledged DeFi protocol with governance: 5–8 months including audit
Cost is calculated individually—contact us for a project estimate.
Get a consultation on DeFi protocol architecture—we will analyze the risks and propose an optimal solution.
