Lookonchain Analysis Reveals Incorrect Configuration of Tender.fi’s Oracle Machine

03/07/2023 11:59 • Crypto & Markets • 86 views

On March 7, according to Lookonchain’s analysis, due to the incorrect configuration of Tender.fi’s oracle machine, only one GMX ($71) was deposited at the beginning of White Hat 0x896d, and about $1.59 million of assets were borrowed.

The configuration error of the Tender.fi oracle machine resulted in a white hat with only one GMX borrowed $1.59 million in assets

Interpretation of the news:

According to Lookonchain’s recent analysis, Tender.fi’s oracle machine had been operating with an incorrect configuration, resulting in a significant financial loss. At the beginning of White Hat 0x896d, only one GMX ($71) was deposited, but approximately $1.59 million worth of assets were borrowed due to this configuration error.

Firstly, it is essential to understand Tender.fi’s oracle machine’s role in the platform’s functioning. It is responsible for retrieving data about the assets, such as the price and liquidity of the market. Thus, the system’s optimal configuration is necessary to ensure that the data obtained is accurate.

In this case, the incorrect configuration of the oracle machine led to inaccurate price data being inputted, leading to a flawed borrowing process for assets leading to significant financial loss. The resulting mispricing could have come from several sources, including a bug in the software used by Tender.fi or even inaccurate pricing data from the external sources such as an unrelated API.

Therefore, this scenario highlights the importance of proper system configuration to prevent such errors that could lead to financial losses. Investors rely heavily on the accuracy of the data obtained by the oracle machine and expect the machine to be configured correctly to prevent incorrect data from circulating throughout the platform.

The Lookonchain analysis provides an insight into the nature of the error that led to Tender.fi’s losses. While it is unfortunate for the platform, it also serves as a valuable lesson to designers and maintainers of similar systems. Comprehensive testing and continual monitoring of the system to detect and remediate bugs or vulnerabilities can ensure the data being inputted is accurate.

In conclusion, the lookonchain analysis provides an interesting insight into the vulnerability of the web-based financial systems that have been implemented. Comprehensive system testing and continuous monitoring will reduce the likelihood of errors leading to financial losses. However, with the ever-changing nature of technology, there needs continuous review and maintenance of systems to ensure user funds are always safe.

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