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Last week, I was helping a friend download a lending app. I was scrolling through screens on the side, occasionally checking the market—cryptocurrency prices were very stable, nothing unusual. Suddenly, a message popped up: "Bro, I got liquidated?" I was stunned, quickly pulled up the K-line chart to check. Upon zooming in, I noticed the clue—a sudden cliff-like candle lasting only a few seconds appeared on a low-liquidity trading pair. Just this abnormal fluctuation caused the app's price feed to treat it as real market data, instantly triggering the liquidation mechanism. My friend's loan went from stable to high risk, and he was liquidated in an instant.
This reveals a core risk in crypto lending: liquidation doesn't necessarily require the entire market to crash; as long as the price source is manipulated, it’s enough. The trick used by bad actors is actually quite simple—find a trading pool with low liquidity, drain funds, then place large sell orders to create a false low price in a short period. Once the oracle captures this manipulated price, the lending protocol perceives the collateral as devalued, triggering a series of liquidations. When the price normalizes, the malicious actor has already bought a large amount of cheap assets at the low point and can walk away unscathed. Victims are left wondering: the market didn't move, so why was I liquidated?
The root of the problem lies in the price feed source. Relying on data from a single exchange is too easy to manipulate; a more robust data aggregation solution is needed. For example, pulling data from multiple trading channels simultaneously, using median and time-weighted average methods to filter out anomalies. This way, even extremely low prices can't sway the overall market trend; short candles lasting a few seconds become insignificant after smoothing. Coupled with periodic refresh mechanisms, outdated data can be rejected in time, and large price jumps can trigger automatic pauses in price assessment.
From an application perspective, besides optimizing the price feed, additional protective measures can be implemented: applying liquidation delays for extreme prices, increasing risk buffers for assets with low liquidity. Only then can the loophole in the lending market be truly sealed.