Tradoor

Security in crypto trading is not just about passing audits. Markets move fast, prices can change before trades settle, liquidity can shift, oracle feeds can lag, and liquidation pressure can build quickly.
That is why Tradoor is designed with protection at multiple levels. We combine external smart-contract audits with AI-driven systems that monitor execution, liquidity, price data, and market stress in real time:
Price Lock to eliminate slippage.Liquidity Shield to protect liquidity.Data Defence to strengthen oracle reliability.ADL to support solvency in extreme markets.
Tradoor has been audited by TonBit and Zellic, with TonBit reviewing the protocol in May 2024 and Zellic reviewing it in May 2025. Tradoor has never been exploited or hacked, but security is not a one-time milestone; it is an ongoing process of testing, monitoring, and improving the protocol as markets evolve.
Why AI matters for protocol security
AI is changing the security landscape because it is making vulnerability discovery faster, more automated, and more accessible.
Anthropic’s Claude Mythos Preview is a recent example: Anthropic describes it as its most capable model for coding and agentic tasks, says it can find and fix software vulnerabilities, and states that it has already identified thousands of zero-day vulnerabilities across critical infrastructure.
If AI can help researchers find weaknesses faster, then defensive systems also need to become faster. Audits remain essential, but live monitoring, automated detection, and adaptive risk controls are becoming just as important for protocols that operate in fast-moving markets.
Tradoor’s AI protection stack
Tradoor uses four core protection systems across the trading stack: Price Lock, Liquidity Shield, Data Defence, and ADL.
Each one addresses a different type of risk, from trade execution and liquidity protection to oracle reliability and system solvency.
1. Price Lock: Zero slippage on pricing
Price Lock is designed to reduce execution uncertainty in fast markets. When a trader places an order, the price shown on screen can change before the trade settles, which can lead to slippage or stale-price execution risk; Tradoor’s Price Lock mechanism is built to help lock the quoted price at the time of order and give traders a more predictable execution experience.
The result is zero price slippage, faster confirmations, and lower gas fees.
AI supports this process by assessing factors such as volatility, trade size, liquidity depth, and recent market movement. The goal is to help determine when a quoted price can be safely honored, so traders receive more consistent execution while the protocol is protected from stale-price arbitrage.
2. Liquidity Shield: Filtering out toxic flow
Liquidity Shield is designed to protect the protocol from toxic flow and arbitrage patterns that can damage liquidity quality. Not all order flow affects a market in the same way: some flow reflects normal trading activity, while other flow may be designed to exploit latency, temporary imbalances, or stale prices.
Liquidity Shield 2.0 is an anti-slippage security filter that safeguards liquidity and protects both the protocol and users from toxic flows and arbitrage attacks. Powered by advanced machine learning, it can identify friendly order flow with over 99% accuracy, which helps protect the integrity of the Price Lock mechanism.
By classifying order flow in real time, Liquidity Shield helps protect liquidity providers, support more reliable execution for traders, and maintain a healthier trading environment across the protocol.
3. Data Defence: Defends price oracle attacks
Price data is one of the most important security layers in any derivatives protocol because it affects execution, PnL, liquidations, and settlement. If a protocol relies on bad or delayed price data, even correctly functioning smart contracts can produce poor outcomes for traders.
Tradoor uses Pyth for real-time price feeds, with Pyth delivering data directly from market participants, such as trading firms and exchanges. The protocol actively fetches the Pyth price updates it needs for trading, liquidations, and pricing, which gives the protocol more control over speed and cost-efficiency.
Tradoor also uses its own private oracle, which pulls real-time feeds from several sources and checks them against Pyth to create an additional verification layer. Data Defence is the AI layer around this oracle system: it helps compare price feeds, detect stale data, flag abnormal deviations, and identify when one source is behaving differently from the broader market.
The objective is to prevent bad market data from becoming bad trades, bad liquidations, or bad settlements.
4. ADL: Protecting liquidity
Auto-Deleveraging, or ADL, is Tradoor’s backstop for extreme market conditions. If a large position closure creates a scenario where net exposure exceeds available liquidity, the system may need to forcibly reduce positions so that traders’ profits still have counterparties for settlement.
AI supports ADL by monitoring leverage concentration, net exposure, volatility, liquidity depth, and liquidation pressure. Instead of waiting until market stress becomes severe, machine learning can help identify when the system is moving closer to dangerous conditions, giving the protocol a better chance to respond before stress turns into a solvency issue.
The takeaway
AI does not remove risk from crypto trading, and it should not be treated as a substitute for audits, sound protocol design, or conservative risk management. Its value is in speed, pattern detection, and adaptability, especially in markets where conditions can change faster than manual systems can respond.
Security is not only about whether code has been audited; it is also about whether the protocol can keep operating safely when markets move quickly, liquidity is tested, and attack methods become more advanced.
That is the standard we are building toward at Tradoor.