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This article focuses on CryptoProver, a system leveraging AI to automatically synthesize formal proofs for cryptographic libraries without altering the underlying executable code. By automating verification tasks previously requiring months of manual effort by human experts, it addresses critical infrastructure security in deployed systems like Signal and Shadowsocks. The approach demonstrates how machine learning can bridge the gap between high-level API contracts and rigorous mathematical guarantees essential for cryptography.
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An AI Approach to Verified Production Cryptographic Libraries

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.00965v1 Announce Type: cross Abstract: Cryptographic code is critical infrastructure that must be correct, yet formally verifying production libraries remains difficult. Existing language-model proof systems solve isolated obligations with specifications and premises already given, leaving production-library verification unresolved. We present CryptoProver, an AI-based system that synthesizes internal specifications and Verus-checked proofs from high-level API contracts. Without changing executable code, CryptoProver constructs a new independent proof of curve25519-dalek and verifies RustCrypto's previously unverified chacha20 implementation against an RFC 8439 specification. These cryptographic lineages underpin deployed systems including Signal and Shadowsocks; Signal has an estimated 218M global downloads. The independent, human-led curve25519-dalek verification was developed publicly over eight months by five main contributors. Given the API contracts and a fixed trusted library of field specifications, arithmetic facts, axioms, and vstd, CryptoProver synthesizes the internal specifications and proofs in 11.4 hours with USD 466.99 in recorded API cost. CryptoProver follows a trust-first design principle: mechanical gates reject specification weakening, invented axioms, and cross-module breakage, while isolation blocks reference proof retrieval, including from git history.

Abstract:Cryptographic code is critical infrastructure that must be correct, yet formally verifying production libraries remains difficult. Existing language-model proof systems solve isolated obligations with specifications and premises already given, leaving production-library verification unresolved. We present CryptoProver, an AI-based system that synthesizes internal specifications and Verus-checked proofs from high-level API contracts. Without changing executable code, CryptoProver constructs a new independent proof of curve25519-dalek and verifies RustCrypto's previously unverified chacha20 implementation against an RFC 8439 specification. These cryptographic lineages underpin deployed systems including Signal and Shadowsocks; Signal has an estimated 218M global downloads. The independent, human-led curve25519-dalek verification was developed publicly over eight months by five main contributors. Given the API contracts and a fixed trusted library of field specifications, arithmetic facts, axioms, and vstd, CryptoProver synthesizes the internal specifications and proofs in 11.4 hours with USD 466.99 in recorded API cost. CryptoProver follows a trust-first design principle: mechanical gates reject specification weakening, invented axioms, and cross-module breakage, while isolation blocks reference proof retrieval, including from git history.

Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)

arXiv:2608.00965 [cs.CR]

(or arXiv:2608.00965v1 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2608.00965 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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