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Moonwell Lending Protocol Lost $1.78 Million Due to Oracle Error

Reading time: 2 min
February 18, 2026
Author: Team Resonance
Moonwell Lending Protocol Lost $1.78 Million Due to Oracle Error

Moonwell lost $1.78 million due to an oracle error related to vibe-coding with Claude Opus 4.6.

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Moonwell Lending Protocol faced losses amounting to $1.78 million after an error in oracle setup. This incident occurred due to shortcomings related to the use of vibe-coding via Claude Opus 4.6.

Technical Aspects

The failure occurred on February 15 following the activation of Moonwell DAO proposal — MIP-X43, which allowed for contracts using Chainlink (a decentralized oracle network) OEV on the Base and Optimism markets.

One of the oracles was improperly configured: instead of correctly calculating the cbETH/ETH rate, it only showed the internal token ratio, resulting in an incorrect valuation of cbETH at $1.12 instead of ~$2200.

Impact on Users

This error caused abnormally low quotes and, consequently, a wave of liquidations swept over users. Trading bots actively exploited the situation, destroying collateral in cbETH and creating significant debts for borrowers. Moonwell representatives promptly attempted to mitigate the risks by reducing borrowing limits for cbETH.

Vibe-coding Under Scrutiny

Pashov, a smart contract auditor, linked the error to the use of vibe-coding and collaboration with the neural network Claude Opus 4.6. The expert noted that although a human checks the code, this incident casts doubt on the widespread use of vibe-coding in software creation.

The Moonwell case is yet another confirmation of the problems arising with the use of automated coding tools. Previous studies have identified numerous vulnerabilities in applications created by these methods.

Conclusion:

The incident with Moonwell prompts reflection on the use of vibe-coding and underscores the importance of strict control and code verification. Code automation systems open new opportunities but demand a responsible approach.

  • Strengths: automation and acceleration of processes.
  • Risks: potential errors and vulnerabilities, especially with unqualified control.
  • Opportunities: improvement and verification of neural network algorithms.
  • Threats: loss of financial resources and user trust.

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