Hyperliquid's whale activity has attracted significant attention.

Recently, the address 0xf3f496c9486be5924a93d67e98298733bb47057c leveraged 50x to go long on ETH on Hyperliquid, with unrealized profits exceeding $2 million. Due to the large position size and the transparent nature of DeFi, the entire crypto market is watching this whale's movements. The public generally believes that the next move will either be to increase the position for higher profits or to close the position to take profits. However, the whale made an unexpected move by withdrawing margin to realize profits, while the system adjusted the liquidation price of the long position upwards. Ultimately, the whale triggered liquidation, making a profit of $1.8 million.

What impact did this operation have? It harmed the liquidity of HLP.

HLP is actively market-making by Hyperliquid, collecting funding fees and liquidation profits. All users can also provide liquidity for HLP.

Due to the high profits of the ETH whale, a normal one-time liquidation would lead to insufficient liquidity on the opposite side. However, by actively seeking liquidation, that portion of the amount was absorbed by HLP, resulting in a reduction of about $4 million in funds in just one day on March 12.

This attack signifies a severe challenge for Perp Dex, necessitating an evolution in the liquidity pool mechanism. Taking this opportunity, WOO X Research will compare the mechanisms used by current mainstream Perp Dexs (Hyperliquid, Jupiter Perp, GMX) and finally discuss how to prevent similar attacks from occurring!

Reference: https://app.hyperliquid.xyz/vaults/0xdfc24b077bc1425ad1dea75bcb6f8158e10df303

Hyperliquid

• Liquidity Provision: Funded by the community liquidity pool HLP (Hyperliquid Pool), users can deposit assets like USDC into the HLP Vault to become market-making liquidity for the platform. Additionally, users are allowed to create their own "Vault" to participate in market-making profit sharing.

• Market-Making Model: Utilizes a high-performance on-chain Order Book matching system, providing a centralized exchange-level experience. The HLP Vault acts as a market maker, placing orders on the order book to provide depth and handle unmatched portions, reducing slippage. Prices are referenced from external oracles to ensure order prices are close to the global market.

• Liquidation Mechanism: Triggers liquidation when the minimum margin (usually starting at 20%) is insufficient. Any user with sufficient capital can participate in liquidation, taking over positions that do not meet the maintenance margin. The HLP Vault also serves as a liquidation insurance fund; if liquidation causes losses, they are borne by HLP (as in this attack).

• Risk Management: Employs multi-exchange price oracles, updated every 3 seconds, to prevent erroneous prices caused by malicious market manipulation. For extreme situations triggered by whale positions, the minimum margin for certain positions has been raised to 20% to reduce the impact of large liquidations on the pool. Anyone can participate in liquidation to enhance decentralization, while a single Vault bears the risk. The downside is that as an emerging proprietary chain, it has not yet undergone long-term testing, and there have been past risks of significant liquidation losses.

• Funding Rates and Position Costs: Funding rates for long and short positions are calculated hourly to anchor contract prices close to spot prices. If longs dominate shorts, longs pay funding fees to shorts (and vice versa) to prevent long-term price deviations. In cases where the platform's net positions exceed HLP's capacity, Hyperliquid reduces risk by increasing margin requirements and possibly dynamically adjusting funding rates. Position costs do not incur additional interest for overnight holdings, but high leverage increases the pressure of funding fee expenditures.

Jupiter

• Liquidity Provision: Funded by the multi-asset JLP (Jupiter Liquidity Pool), which includes index assets like SOL, ETH, WBTC, USDC, and USDT. Users mint JLP by swapping assets, with JLP acting as the counterparty to bear the risks of leveraged trading.

• Market-Making Model: Abandons the traditional order book in favor of an innovative LP-to-Trader mechanism. Through oracle pricing, traders can directly trade with the JLP liquidity pool, enjoying a near-zero slippage trading experience. Advanced features like limit orders can be set, but in essence, trades are filled by the pool at oracle prices.

• Liquidation Mechanism: Automatically liquidates when the margin rate of a position falls below the maintenance requirement (e.g., 6.25%), with smart contracts automatically closing positions at oracle prices. The JLP liquidity pool absorbs the profits and losses of that position, and if a trader is liquidated, the remaining margin belongs to the pool. Users can adjust collateral during the position period to modify the liquidation price, but excessive collateral withdrawal can bring the liquidation price closer to the current price, making liquidation more likely.

• Risk Management: Uses oracles to keep contract prices closely aligned with spot prices, avoiding price manipulation. The high TPS of the Solana chain reduces liquidation lag risk, but instability in the underlying network can affect trading and liquidation. To prevent malicious manipulation, the platform can set limits on the total position of a single asset (e.g., limiting maximum leverage positions), while borrowing rates increase with asset utilization, raising the cost of long-term unilateral positions and curbing extreme bias. To date, traders are overall in net losses, while JLP funds have steadily increased.

• Funding Rates and Position Costs: Jupiter Perp does not have traditional funding rates; instead, it uses borrowing fees (0.01% charged hourly based on the proportion of borrowed assets in the pool). This fee is directly paid to the GLP pool, meaning that regardless of long or short positions, holders must pay holding interest, which is included in position profits and losses. The higher the asset utilization, the higher the annualized borrowing fee (which can exceed 50%), economically punishing long-term crowded positions.
  In this model, perpetual prices remain close to spot prices (zero slippage), with no traditional funding rate imbalance, but the pool must bear profits and losses during significant price fluctuations.

GMX

• Liquidity Provision: Funded by the multi-asset index pool GLP (GMX Liquidity Pool), which includes assets like BTC, ETH, USDC, and DAI. Users deposit assets to mint GLP, which becomes the counterparty for all trades, bearing trading profits and losses.

• Market-Making Model: Lacks a traditional order book, using oracle pricing and pool assets to automatically act as the counterparty. GMX uses Chainlink's decentralized oracles to obtain market prices and execute trades with "zero slippage." The GLP asset pool acts as a unified market maker, adjusting pool assets through a price impact fee mechanism to ensure liquidity depth.

• Liquidation Mechanism: Automatically liquidates using Chainlink index prices to calculate position value. When the margin ratio falls below the maintenance level (e.g., approximately 1.25 times the initial margin), liquidation is triggered. During liquidation, contracts are automatically closed, with user margins first used to cover pool losses, and any remaining (if any) returned or included in insurance. The GLP asset pool directly bears losses or gains from liquidation as the counterparty.

• Risk Management: Utilizes authoritative multi-source oracles to reduce wash trading manipulation risks, avoiding erroneous liquidations caused by abnormal fluctuations in a single trading pair. There have been instances where traders exploited GMX's zero slippage mechanism to manipulate prices for arbitrage, leading the team to set maximum opening limits for easily manipulated assets like AVAX (e.g., a limit of $2 million position). Through such position limits and dynamic fee mechanisms (the higher the asset utilization, the higher the holding interest), leverage risks are restricted, while 70% of trading fees are rewarded to GLP to enhance LPs' motivation to withstand losses.

• Funding Rates and Position Costs: GMX V1 does not have mutual funding payments between longs and shorts; instead, it charges borrowing fees (0.01% per hour based on the proportion of borrowed assets). This fee is directly paid to the GLP pool, meaning that regardless of long or short positions, holders must incur holding interest, which is included in position profits and losses. The higher the asset utilization, the higher the annualized borrowing fee (which can exceed 50%), economically punishing long-term crowded positions.
  In this model, perpetual prices remain close to spot prices (zero slippage), with no traditional funding rate imbalance, but the pool must bear profits and losses during significant price fluctuations.

Simple Comparison Table of Hyperliquid vs. Jupiter vs. GMX

Conclusion: The Inevitable Path for Decentralized Contract Exchanges

This attack exploited the decentralized nature of Perp Dex: transparency, with rules determined by code.

The overall attack strategy was to profit through a massive position, attacking the liquidity within the exchange.

To prevent this in the future, it is essential to reduce user position sizes, which can be addressed through leverage ratios and margin requirements. They have also announced a reduction in the maximum leverage ratios for BTC and ETH, adjusting them to 40x and 25x, respectively, and increasing the required margin transfer ratio by 20%. The overall goal is to prevent users from opening large positions.

Following this line of thought, what else can Hyperliquid do? Automatic Deleveraging (ADL).

When the risk reserve (HLP) cannot bear further losses from liquidated positions, an automatic deleveraging (ADL) mechanism will be activated to limit further losses of the risk reserve. The core principle is that losing positions will hedge against profitable positions or high-leverage positions (i.e., "positions to be deleveraged"), with both positions offsetting each other and being closed simultaneously. Due to the activation of the ADL mechanism, profitable positions may be forcibly closed, limiting the future profit potential of those positions while avoiding impacting the HLP vault level.

All these measures are actually limiting a single account. If someone intends to exploit rule loopholes, they can open multiple accounts to carry out similar attacks. Of course, the project team can use address tracking associations to ban related accounts to prevent witch attacks (this is also one of the reasons why centralized exchanges require KYC). However, this measure contradicts the core idea of DeFi - allowing anyone to use decentralized finance without permission.

The best solution is for the Perp Dex protocol itself to mature with the market, gradually thickening liquidity, raising costs for attackers until it becomes unprofitable, and the current predicament is an inevitable path for the development of the sector.

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