Hyperliquid just underwent a "stress test": From a real attack to lessons in defense

Recently, a notable event occurred at Hyperliquid — one of the most advanced decentralized perpetual contract exchanges today. An attacker deliberately burned $3 million of their own funds, but in the end, the protocol’s HLP treasury suffered a $5 million loss — nearly double the amount wiped out by the attacker. This serves as a valuable lesson on the resilience of decentralized trading systems.

On the surface, this incident appears to be a completely unprofitable “suicide attack” — no winners, only casualties. However, upon closer inspection, we can see it might be a low-cost “stress test” targeting Hyperliquid’s actual defensive capabilities. Especially considering that if this method remains open, larger capital players could potentially upgrade it to a bigger scale.

How the entire attack unfolded

The scenario begins very simply: the attacker withdraws $3 million USDC from a centralized exchange, then disperses this amount into 19 different wallets to hide traces. Next, all funds are sent into Hyperliquid.

Within the protocol, the attacker makes a pivotal move: opening a long position with 5x leverage on the HYPE/POPCAT pair. With $3 million as margin, they control a position size of up to $26 million. Up to this point, everything follows normal rules.

But what changes everything is in the next detail: the attacker places a massive buy wall — $20 million — at $0.21, while the price is fluctuating near $0.22. This creates an illusion of strong support, sending a clear market signal: “There’s a huge investor here, the price will definitely struggle to fall below this level.”

Other traders, seeing this positive flow of capital, trust that the support wall will prevent any collapse. They start opening long positions or fail to manage risk properly, trusting in that support. Liquidity concentrates on one side, and leverage gradually accumulates.

At this moment, the attacker pulls the fake buy wall off the order book. Immediately, liquidity disappears, and there’s no real support left. The price begins to fall. Traders using leverage get liquidated in a cascade effect — each liquidation triggers more sell-offs, leading to further liquidations.

By the end of this chain reaction, many traders are wiped out, but the system’s mechanism has forced the HLP treasury of Hyperliquid to absorb a $4.9 million loss.

What is HLP and why does it suffer?

To understand better, we need to look into HLP — short for Hyperliquid Pool. You can think of it as a large shared treasury, mainly consisting of USDC, acting as the final counterparty for all traders on the platform.

Its operation is straightforward:

• Users deposit USDC into HLP
• In return, they provide liquidity to the system and accept risk
• When traders lose, they profit; when traders win, the treasury pays out

In other words: if the market is stable, HLP will profit because losing traders offset winning traders. Theoretically, the treasury should stay balanced.

In practice, HLP has performed very well. Since inception, the treasury has accumulated a net profit of $118 million. This $5 million attack is only about 4% of that accumulated profit.

However, the core issue lies here: in a normal market, traders are liquidated before their accounts are completely wiped out, and their losses are offset by winners. The system remains balanced.

But in a crash like this attack:

• Price volatility is too rapid, exceeding response capabilities
• Liquidity disappears exactly when it’s most needed
• Some positions cannot be closed at reasonable prices
• Slippage becomes horrific
• Liquidation proceeds are insufficient to cover winners

This gap — between what traders would have lost and what the system actually collects — is borne by the HLP treasury. This is the biggest protocol safety risk.

Did the attacker really lose $3 million?

Likely not. A professional attacker probably hedged their position elsewhere — perhaps on a centralized exchange, through options, other perpetual contracts, or OTC agreements.

For example, they might:

• Open a short position on POPCAT on another platform to hedge
• Use OTC deals with partners who benefit from Hyperliquid’s damage
• Build market-neutral, riskless trades profiting from market imbalances in Hyperliquid

We have no public evidence, but from game theory and capital efficiency perspectives, this explanation makes much more sense.

If so, the attacker’s real profit/loss is approximately zero or even positive, while Hyperliquid bears a clear $5 million loss. That’s the real issue.

Lessons for protocols: what kind of defense is needed?

From a professional attacker’s perspective, this attack could be just a low-cost “power test” — enough to observe how the system reacts, the true depth of the treasury, the team’s response speed, and whether emergency measures are effective. It’s a prelude to larger, better-coordinated attacks in the future.

To defend against such attacks, Hyperliquid and similar protocols should implement a series of measures:

Limit individual risk: Restrict the amount of risk a single entity can accumulate, even if they split across multiple wallets. Use heuristic methods like analyzing cash flow models, timing, IP, and behavioral patterns.

Adaptive margin requirements: When one side of the order book is severely skewed, enforce stricter margin requirements to prevent excessive position accumulation.

Circuit breaker mechanisms: Apply circuit breakers to each market, especially those with low liquidity. When prices move too rapidly under thin liquidity and high open interest, automatically switch to defensive mode, slowing trading activity. This gives the system time to react before the HLP absorbs too much damage.

Strict rules for low-liquidity assets: These are more susceptible to manipulation, so higher restrictions are necessary.

Fake order detection: Improve detection of spoof orders and “fake buy walls” to prevent the system from relying on misleading liquidity signals.

Smarter HLP: The HLP itself can evolve from a passive counterparty to a more intelligent mechanism, automatically hedging extreme risks on external exchanges, or even splitting into a conservative part and a volatile, optional part.

In summary, the key is that when someone attempts to build a position capable of destroying the system, the protocol must switch to a defensive mode before the treasury absorbs the damage. This is the way for decentralized protocols to become truly resilient.