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NewsTopic · Lean形式化验证信任Material2 min readDisconfirmAI Editorial

Lean Creator Leonardo de Moura: How a Claimed Proof Suspectedly Exploited Different Vulnerabilities to Bypass Two Independent Kernels

In the September 30, 2026 episode of Machine Learning Street Talk, Lean theorem prover creator Leonardo de Moura recounts how two independent checkers were deceived by different vulnerabilities in the Collatz proof incident, and discusses the architecture design of small trusted kernels and independent verifiers.

2026-09-30 11:19 GMT+8

A piece of Lean code claiming to prove the Collatz conjecture passed verification from both the official Lean kernel and an independent checker, Nanoda—yet it appears each exploited a different vulnerability to do so. This is the account given by Leonardo de Moura, creator of the Lean theorem prover, on the September 30, 2026 episode of Machine Learning Street Talk. The episode was hosted by Tim Scarfe and lasted seventy-four minutes.

The program begins with why Lean deliberately maintains an extremely small trusted kernel, extending to the original intent and limitations of independent checkers. De Moura discussed introducing more checkers, the risks of reward hacking, achieving safety through transparency, and responded to governance questions regarding who controls the core of Lean.

De Moura founded Lean at Microsoft Research in 2013, initially with the goal of checking software code for correctness; he is also the co-creator of the SMT solver Z3. According to a book review in Science News, mathematicians and AI researchers have now become Lean's most active users. This episode also covers Lean's evolution from Lean 1 to Lean 4, how dependent types and Mathlib made formal proofs accessible to professional mathematicians, the role of AI agents in proof search ("breadcrumbs" rather than learning), and why certificates remain important in the era of AlphaProof and large language models.

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It should be noted that the above descriptions of the Collatz incident and kernel topics are summaries from the official show notes of the program, not a verbatim transcript. De Moura's specific arguments, judgments on governance models, and analysis of AI agent limitations require listening to the full program to evaluate. For readers interested in the reliability of formal verification, AI-generated proofs, and whether "automatic checking" can truly replace human scrutiny, this episode provides a first-hand perspective from the system's creator.

Sources

  • podcasters.spotify.com↗
  • sciencenews.orgScience News↗
Topic

Lean形式化验证信任

Lean定理证明器作为数学与代码正确性的“真理机器”,其核心价值在于通过极小的可信内核实现逻辑验证,但近期暴露的信任危机揭示了自动化证明的深层局限。2026年9月,创始人Leonardo de Moura披露Collatz猜想证明事件中,两…

5 steps1 piecesUpdated 2026-10-26 09:44

How it got here

  1. 2013-01-01Leonardo de Moura在微软研究院推出Lean,旨在通过小可信内核验证软件代码正确性。sciencenews.org ↗
  2. 2024-07-01Google DeepMind的AlphaProof在国际数学奥林匹克中获银牌水平成绩,推动AI与Lean结合的趋势。sciencenews.org ↗
  3. 2026-07-01Lean 4.32.1和4.32.2版本修复了两个内核漏洞,这些漏洞曾被利用以证明False。invarians.org ↗

What is still unsettled

  • 在AI自动生成证明日益普及的情况下,如何建立标准化的流程来检测并防止‘语义幻觉’(即逻辑正确但含义错误)?
  • 除了依赖多个独立的外部检查器(如Lean4Lean),是否有更根本的方法能消除对硬件、操作系统及编译器本身的信任依赖?
  • 对于像C-HD这样理论复杂度优于经典算法但实际性能较差的案例,形式化验证应如何纳入工程实用性的评估维度?
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