Ethereum Team Explains How AI Is Changing the Approach to Smart Contract Security

cryptonews.ruPublished on 2026-08-06Last updated on 2026-08-06

Abstract

The Ethereum team published a guest post series by a leading Vyper developer under the pseudonym "big_tech_sux," focusing on the role of formal verification in the era of rapidly advancing AI. The author argues that progress in Large Language Models (LLMs) is making the mathematical proof of program correctness more accessible. For smart contracts managing billions of dollars, formal verification is gradually becoming a necessity. Formal verification is a mathematical method that proves a program works correctly for all possible execution scenarios, not just those covered by tests. It can find extremely rare bugs that are practically impossible to detect through conventional testing. While previously requiring large teams of experts, modern LLMs significantly simplify this process as they approach Artificial General Intelligence (AGI). However, the author notes that formal verification remains complex and resource-intensive, even with AI assistance. The development of AI simultaneously increases the effectiveness of both defenders and attackers. Formal verification can shift the advantage toward defenders, as they can use it to prove a system's resilience to *all* possible inputs, whereas an attacker only needs to find one exploitable sequence. Therefore, for critical software like high-value smart contracts, formal verification is becoming "not an option, but a necessary prerequisite." This continues a discussion previously initiated by Ethereum co-founder Vitalik Buterin ...

The Ethereum network team has published a guest series of posts from a leading Vyper developer under the pseudonym big_tech_sux, dedicated to the role of formal verification in the era of rapid artificial intelligence development.

The author argues that progress in LLMs is making mathematical proof of program correctness more accessible, and for smart contracts managing billions of dollars, formal verification is gradually becoming a necessity.

AI Is Changing the Approach to Software Verification

The series explains that formal verification is a mathematical method that allows proving the correctness of a program's operation for all possible execution scenarios, not just those covered by tests.

As an example, the author cited the function f(x) = x/2, for which one can mathematically prove that the result will never exceed the input value.

According to them, this methodology can find extremely rare bugs that are practically impossible to detect through ordinary testing.

"Formal verification can detect one case in a quadrillion that will never appear during testing, but it is precisely this case that can lead to a catastrophic failure," the author noted.

At the same time, they acknowledged that until recently, using this approach required the work of large teams of experts who created mathematical models of programs and conducted complex proofs.

In the developer's opinion, modern LLMs significantly simplify this process as we move closer to AGI.

However, the author emphasized that even with the help of AI, formal verification remains a complex and resource-intensive process. In particular, converting program code into a formal model can contain inaccuracies that affect the reliability of the results.

The Development of AI Changes the Balance Between Attack and Defense

The material notes that the development of artificial intelligence simultaneously increases the effectiveness of both defenders and attackers.

The author recalled a case where an unreleased OpenAI model was able to find zero-day vulnerabilities that allowed bypassing multiple layers of protection.

Against this backdrop, formal verification, according to the author, allows shifting the advantage in favor of defenders.

"While attackers only need to find one sequence of input data to hack a system, defenders can use formal verification to prove its resilience to all possible input data," they emphasized.

This is precisely why for critical software, particularly smart contracts managing billions of dollars in user funds, formal verification is becoming "not an option, but a necessary prerequisite."

It is worth noting that this continues a discussion previously initiated by Ethereum co-founder Vitalik Buterin regarding the use of AI for formal code verification.

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Related Questions

QWhat is the main topic discussed in the Ethereum team's guest post series, according to the article?

AThe main topic is the role of formal verification in the era of rapidly developing artificial intelligence, particularly for smart contracts.

QHow does the article define 'formal verification'?

AFormal verification is defined as a mathematical method that allows proving the correct operation of a program for all possible execution scenarios, not just those covered by tests.

QAccording to the author, what is the significance of large language models (LLMs) for formal verification?

AThe author states that the progress of LLMs is making the mathematical proof of program correctness more accessible and is significantly simplifying the formal verification process as technology moves closer to Artificial General Intelligence (AGI).

QWhy does the author argue that formal verification is becoming a necessity for smart contracts?

ABecause smart contracts manage billions of dollars in user funds, and formal verification allows defenders to prove a system's resilience against all possible inputs, shifting the advantage from attackers to defenders.

QWhat potential flaw in the formal verification process does the author acknowledge, even with the help of AI?

AThe author acknowledges that converting program code into a formal model can contain inaccuracies, which affects the reliability of the verification results, and that the process remains complex and resource-intensive.

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