IsabeLLM: Automated Theorem Proving Applied to Formally Verifying Consensus

2026-06-16

AI Summary

This work addresses the challenge that formal verification of blockchain consensus protocols heavily relies on expert knowledge and remains inaccessible to a broader audience. To overcome this limitation, the authors enhance the IsabeLLM automated theorem-proving framework by integrating, for the first time within the Isabelle/HOL environment, retrieval-augmented generation (RAG), error tracing, and counterexample generation mechanisms, while ensuring compatibility with the latest versions of Isabelle and Sledgehammer. This integration substantially improves the reasoning capabilities and contextual understanding of large language models in verifying consensus protocols. Experimental evaluation demonstrates that the enhanced IsabeLLM achieves significantly higher efficiency and success rates than the original version in the formal verification of Bitcoin’s proof-of-work protocol.

Abstract

Advances in Artificial Intelligence (AI) have led AI for Theorem Proving to become a promising means of formally verifying computer systems. Whilst formal verification is traditionally reserved for safety-critical systems due to the required amount of expertise and effort, AI can help to automate a large amount of this workload and make it far more accessible. Blockchain-based systems are becoming increasingly popular and are frequently targeted by malicious actors, often resulting in huge financial losses, highlighting the need to better verify these systems and mitigate vulnerabilities. Arguably the most important component of these systems is the consensus protocol, which allows nodes to agree on decisions in a potentially adversarial environment. In this paper, we improve upon IsabeLLM, the automated theorem proving tool in Isabelle. Namely, we implement a Retrieval-Augmented Generation framework, Error tracing and counterexample generation for improved context supplied to the Large Language Model. Compatibility with the latest version of Isabelle and Sledgehammer is also implemented for improved efficiency. We compare the performance of the two versions of IsabeLLM in their ability to complete the verification of Bitcoin's Proof of Work consensus.

Problem

• formal verification
• consensus protocol
• blockchain security
• automated theorem proving
• vulnerability mitigation

Innovation

• Retrieval-Augmented Generation
• Automated Theorem Proving
• Formal Verification
• Consensus Protocol
• Large Language Model