An AI Approach to Verified Production Cryptographic Libraries
arXiv SecurityArchived Aug 04, 2026✓ Full text saved
arXiv:2608.00965v1 Announce Type: new 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 changin
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✦ AI Summary· Claude Sonnet
Computer Science > Cryptography and Security
[Submitted on 2 Aug 2026]
An AI Approach to Verified Production Cryptographic Libraries
Chuyue Sun, Su Fong, Zhiyi Kuang, Yizheng Jiao, Nina Narodytska, Haoze Wu, David L. Dill, Clark Barrett
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.
Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)
Cite as: arXiv:2608.00965 [cs.CR]
(or arXiv:2608.00965v1 [cs.CR] for this version)
https://doi.org/10.48550/arXiv.2608.00965
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Submission history
From: Chuyue Sun [view email]
[v1] Sun, 2 Aug 2026 03:32:08 UTC (146 KB)
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