The Evolution of Trading Information Security
Decentralized trading promises transparency, but where should that transparency end? As DeFi perpetuals markets mature, a critical question has emerged: should your trading positions be visible to everyone, or should strategic information remain confidential while execution stays verifiable?
Recent incidents have brought this question into sharp focus. From alleged exchange insider leaks to architectural transparency that enables predatory behavior, large traders are discovering that information exposure has become one of their biggest risks. The architecture you trade on increasingly determines whether you're hunting alpha or being hunted yourself.
Why it matters: Understanding how different platforms handle trading information helps traders choose infrastructure that protects their strategies rather than exposing them to exploitation.
Case Study 1: The Momentum Finance Liquidation Hunt (November 2025)
What Happened
In early November 2025, Momentum Finance (MMT) experienced coordinated liquidation hunting that wiped out $127 million in positions within 24 hours. Of that total, $114 million came from short liquidations while only $12.59 million came from longs. The one-sided nature of the liquidations immediately raised suspicions.
According to industry sources who spoke with Chinese crypto media, this wasn't simply aggressive market making or natural volatility. The attack allegedly involved exchange insiders sharing whale short position details directly with market makers, including specific margin ratios and liquidation prices for large accounts.
The Mechanics of Precision Targeting
Normally, market participants work with aggregate data: overall open interest, long/short ratios, general positioning trends. Market makers already have advantages in information access and capital, making retail traders play with partially visible hands.
But market makers typically don't know individual user specifics:
Exact position sizes for large accounts. While they can estimate based on order flow, precise exposure numbers remain hidden.
Specific margin ratios and available collateral. How close a whale is to liquidation depends on their account-level math, not visible in aggregate data.
Precise liquidation trigger prices. Without knowing exact leverage and margin on individual positions, liquidation levels must be estimated rather than calculated.
When exchange insiders allegedly leaked this data for Momentum Finance shorts, the game changed completely. Armed with precise liquidation prices, market makers could engineer "custom-tailored" pump paths designed to trigger specific whale liquidations surgically. The result was devastating precision in wiping out large positions.
Key evidence: Liquidation prices differed across exchanges, suggesting attacks were coordinated based on exchange-specific position data rather than market-wide analysis. If this were natural market movement, liquidation patterns would have been more uniform across platforms.
The Coordinated Attack Strategy
Beyond the information leak, the Momentum Finance incident involved multiple coordination elements:
The project team and market makers allegedly delayed airdrop distribution to control token supply, making price manipulation easier with reduced circulating supply.
The pump occurred during Asian nighttime hours when many traders were asleep and unable to respond to margin calls or adjust positions.
Market makers used the leaked position data to identify exact price levels that would trigger cascading liquidations, then systematically pushed prices to those levels.
Industry sources indicated the exchange involved was not Bybit or Binance, though they declined to name it specifically due to inability to verify evidence conclusively. Community analysis identified Amber as Momentum Finance's market maker, though it's unclear if other parties participated.
Case Study 2: Hyperliquid's Structural Transparency Problem
The Architecture of Exposure
Beyond insider leaks at centralized venues, some decentralized platforms have made transparency their defining feature, creating similar vulnerabilities through architecture rather than misconduct. Hyperliquid operates a fully on-chain order book where every transaction becomes publicly visible in real time.
How it works: Hyperliquid runs on its own dedicated Layer 1 blockchain with a fully on-chain central limit order book. The platform achieves impressive performance with up to 200,000 transactions per second and has captured roughly 78.8% of DEX perpetuals market share.
The transparency trade-off: Every limit order, trade, position, and liquidation gets recorded on-chain at what Hyperliquid calls "L4 granularity." Individual orders are completely public with no information disparity between participants. Anyone can monitor market depth and specific wallet activity directly on-chain or via analytics tools.
When Visibility Enables Predation
This architectural transparency creates exploitable attack vectors that don't require insider access:
Front-running becomes straightforward. When large buy orders hit the blockchain, trading bots can detect the size, price, and wallet address. They buy ahead of the whale, push prices up, then sell back at higher levels before the whale's order completes.
Liquidation hunting becomes profitable. When a whale's position and liquidation price are publicly calculable from on-chain data, other actors can deliberately drive the market toward that trigger point and profit from the liquidation cascade.
Coordinated manipulation becomes feasible. Multiple actors can identify the same vulnerable positions and coordinate attacks against them using publicly available data.
The XPL Short Squeeze (August 2025)
The risks of structural transparency materialized dramatically in August 2025. A coordinated group targeted the XPL token on Hyperliquid, pumping millions into the thinly traded market within minutes and sending the price up over 200%.
The impact:
Mass liquidations cleared the order book and triggered forced closures of short positions.
An estimated $50 million in losses hit other traders while the attacking group profited around $38 million.
Affected users described being "hunted down badly" despite using relatively conservative leverage.
The response: Hyperliquid's team introduced safeguards after the incident, including 10x price move caps on illiquid markets. However, the event revealed how transparent architectures enable predatory behavior at a fundamental level. When positions are public and liquidation levels are calculable, coordinated attacks become not just possible but profitable.
The philosophical divide: Hyperliquid's team argues that transparency actually improves execution by attracting liquidity to large orders. They claim "markets are efficient machines" and that visibility enables better fills. This assumes benign behavior from participants. The empirical evidence suggests otherwise.
Case Study 3: The Spartan Group Warning (November 2023)
The First Public Disclosure
The Momentum Finance and Hyperliquid incidents have precedent. In November 2023, Kelvin Koh, founding partner at The Spartan Group, made a startling public statement about information security at centralized exchanges.
What he revealed: "Today, we were surprised to learn from one of our industry contacts that a major cryptocurrency exchange (CEX) we are trading on had leaked our short positions to them. This is a significant breach of customer confidentiality and we will cut off our trading activities on the exchange."
The leak involved The Spartan Group's position information being shared with a project that had no business relationship with the firm. The project somehow knew details about The Spartan Group's trading positions.
The Systemic Concern
What made this incident particularly disturbing wasn't just that the leak happened, but how casually the information changed hands. Koh questioned whether any employee at the exchange could access customer trading positions and share them with outside parties.
His assessment: "If any employee of an exchange can learn about customer trading positions and share them with anyone, the exchange does not have appropriate controls. This is one of the largest exchanges we are talking about. This is why centralized exchanges need to be regulated and subject to greater scrutiny."
Koh declined to name the exchange publicly, saying only that it was a large, unregulated platform. He acknowledged having no hard evidence proving the exchange was directly responsible, but the leak clearly occurred through someone with access to their trading data.
The Broader Implications
The Spartan Group incident highlighted systemic vulnerabilities in how trading platforms handle confidential information:
Access controls matter. Even at major exchanges, information governance can be surprisingly loose, with more employees having position data access than traders realize.
Audit trails aren't enough. While modern exchanges implement audit logs for data access, determined insiders can still extract and share information when financial incentives are large enough.
Regulatory gaps persist. Unregulated exchanges face fewer consequences for information security breaches, creating weaker incentives to invest in proper controls.
The warning from 2023 proved prescient. Two years later, the Momentum Finance incident suggests similar information leakage continues at some venues, now allegedly weaponized in coordination with market makers for systematic liquidation hunting.
How Confidential Execution Solves the Problem
The zkRollup Architecture Advantage
ApeX Protocol addresses information exposure through fundamentally different architecture. Built on zkRollup technology using StarkWare's engine and zkLink network, ApeX separates trade execution from public visibility while maintaining cryptographic verifiability.
How it works:
Trade matching occurs off-chain in a high-speed rollup environment. Order details and positions don't broadcast on a public blockchain in real time.
Periodically, cryptographic validity proofs get posted to Ethereum. These proofs verify that all off-chain activity was legitimate without revealing specific details of individual trades.
All custody remains on-chain through smart contracts. Users maintain true self-custody, and withdrawals can be forced on Layer 1 even if the exchange infrastructure fails.
What Stays Confidential
ApeX's architecture keeps strategic information confidential:
Position sizes remain hidden. Other market participants cannot scan ledgers to identify that specific wallets are placing million-dollar orders or building large positions.
Liquidation levels stay private. Liquidation hunters cannot target positions because they don't know where trigger points sit. The information exists within the rollup's internal state but isn't exposed as readable data on block explorers.
Order flow remains invisible. There's no public mempool where bots can spot pending orders and front-run them before execution.
What Stays Verifiable
Confidential execution doesn't compromise transparency where it matters:
Cryptographic proof of validity. All trades settle with deterministic finality enforced by zero-knowledge proofs. The mathematical verification confirms trades are legitimate without information disclosure.
Ethereum-grade security. Anyone can verify that Layer 2 state updates correspond to real executed trades and that no funds were created improperly.
Non-custodial guarantees. Users retain control of funds at all times through on-chain smart contracts, even if off-chain components fail.
Protection Against Multiple Attack Vectors
The confidential architecture defends against both insider leaks and structural transparency problems:
Against insider leaks: Because matching happens off-chain and only aggregate proofs get posted on-chain, there's no on-chain data for insiders to extract and share. Position details are validated through zero-knowledge proofs but not exposed as readable information.
Against front-running: Pending orders aren't visible in public mempools. Trading bots cannot detect large orders coming and position ahead of them.
Against liquidation hunting: Even the sequencers and validators have limited ability to exploit order information. Any invalid sequencing would be caught by proof verification when batches submit to Layer 1.
Against coordinated manipulation: Attackers cannot identify which whales to target because position information and liquidation levels remain confidential throughout the trading lifecycle.
Why Confidential Trading Infrastructure Matters
The Practical Impact for Whale Traders
Recent events demonstrate what happens when position information becomes accessible, whether through insider access or structural transparency. For serious traders, confidential execution provides categorical protection:
You can execute substantial orders without broadcasting intent. No bots monitoring mempools, no competitors watching your wallet address, no market makers front-running based on visible order flow.
You can hold leveraged positions without revealing liquidation triggers. Predatory actors cannot calculate your exact liquidation price and systematically push markets to trigger it.
You can implement complex strategies without every step being visible. Multi-leg orders, scaling into positions, risk management adjustments all happen without public exposure until settlement.
The Industry Trend Toward Confidentiality
The pattern is clear across recent incidents:
Momentum Finance (2025): Alleged insider leak of position data enabled precision liquidation hunting with $114 million in short liquidations.
Hyperliquid XPL (2025): Structural transparency enabled coordinated manipulation causing $50 million in losses through publicly visible liquidation levels.
Spartan Group (2023): Position leak at major CEX demonstrated how easily confidential information gets shared when controls are weak.
Industry analysis confirms that off-chain order books with on-chain settlement reduce pre-exposure of transaction information, effectively suppressing MEV behaviors compared to fully transparent structures. The confidential execution that zkRollup technology enables isn't incremental improvement over transparent architectures. It's categorical protection against information-based exploitation.
Battle-Tested Infrastructure
ApeX's approach benefits from proven technology rather than novel implementations:
StarkEx has processed over $1 trillion in cumulative volume across applications, demonstrating security and reliability at scale.
zkLink's canonical bridge approach avoids custom implementation risks that create novel attack vectors.
Zero major exploits or significant outages in ApeX's operational history, contrasting with incidents at platforms using custom infrastructure.
The security model doesn't depend on trusting exchange operators, validator behavior, or information governance policies. Mathematical proofs enforce correctness while confidential execution protects strategic information.
Conclusion: Architecture Determines Security
Recent events have demonstrated the real costs when position information becomes accessible. At centralized venues, insider access enables leaks. At transparent decentralized platforms, the architecture itself exposes positions to predatory actors.
Confidential execution through zkRollup technology solves both problems at the architectural level. Strategic information stays protected through cryptographic design while zero-knowledge proofs verify trade validity without exposing position details, order flow, or liquidation triggers.
For whale traders evaluating where to execute size, the question is straightforward: trade where positions can be leaked or read off a public blockchain, or choose confidential execution where your strategy remains your own. The blockchain verifies everything either way. The difference is whether everyone else gets to see your positions and exploit them before you execute.