mlsanityData to 13 Oct 2026

An AI Approach to Verified Production Cryptographic Libraries

arXiv 2608.00965 ↗First posted 2 Aug 2026cs.CR cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 19 of its 32 references that are in the map. First posted on arXiv 2 Aug 2026.

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19 of 32 references.

References · 19

  1. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,412
  2. 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Modelscited by 420
  3. 2025DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decompositioncited by 280
  4. 2023Clover: Closed-Loop Verifiable Code Generationcited by 64
  5. 2023Verus: Verifying Rust Programs using Linear Ghost Types (extended version)cited by 51
  6. 2023Lemur: Integrating Large Language Models in Automated Program Verificationcited by 49
  7. 2024AutoVerus: Automated Proof Generation for Rust Codecited by 46
  8. 2024AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinementcited by 33
  9. 2025VERINA: Benchmarking Verifiable Code Generationcited by 31
  10. 2025A benchmark for vericoding: formally verified program synthesiscited by 17
  11. 2025VeruSAGE: A Study of Agent-Based Verification for Rust Systemscited by 11
  12. 2025VeriStruct: AI-assisted Automated Verification of Data-Structure Modules in Veruscited by 8
7 more
  1. 2026KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Codecited by 5
  2. 2025Towards Repository-Level Program Verification with Large Language Modelscited by 4
  3. 2026Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systemscited by 3
  4. 2017Verified Correctness and Security of mbedTLS HMAC-DRBGcited by 1
  5. 2019The Last Mile: High-Assurance and High-Speed Cryptographic Implementationscited by 1
  6. 2026A Rust-to-Lean Verification Pipeline with AI Provers: An Experience Reportcited by 1
  7. 2026Automating Formal Verification with Reinforcement Learning and Recursive Inferencecited by 1

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