{"slug": "ai-grinding-for-fun-and-cryptanalysis", "title": "AI Grinding for Fun and Cryptanalysis", "summary": "A new arXiv preprint (submitted Aug 22, 2026) presents an autonomous cryptanalysis workflow where AI agents generate, test, and refine hypotheses before human review, finding that eight published cryptographic constructions fail at stated parameters or claims. The failures include a Ring-LWR commitment that opens to every message with probability one, a ciphertext revealing two middle-product encryption rows, a lattice e-voting protocol losing receipt-freeness, and a permutation-recovery attack against updatable encryption extending to the old decryption key. The workflow returns reproducible candidates with exact witnesses, controls, code, and run records, and also identifies three targets with no attack but narrower guarantees than a generic reading suggests.", "body_md": "# Computer Science > Cryptography and Security\n\n[Submitted on 22 Aug 2026]\n\n# Title:AI Grinding for Fun and Cryptanalysis\n\n[View PDF](/pdf/2608.21986)\n\n[HTML (experimental)](https://arxiv.org/html/2608.21986v1)\n\nAbstract:We present an autonomous cryptanalysis workflow in which agents generate, test, and refine hypotheses before human review. The autonomous stage returns reproducible candidates with exact witnesses, controls, code, and run records. A researcher then decides whether the evidence establishes a break, defect, or coverage gap.\n\nTwo failure modes recur. First, a public algebraic map or input representation erases or exposes a relation that a construction must hide. Examples include multiplication by zero, boundary coefficients of a polynomial product, quotients, characters, Schur squares, and variable-length byte encodings without boundaries. Second, a simulator, error law, or parameter certification uses a distribution different from the one claimed. Several targets fail in both ways.\n\nEvery result has an exact witness and a discriminating control; every stated boundary has a proof. Three further targets yielded no attack but support narrower guarantees than a generic reading suggests.\n\nEight published constructions fail at stated parameters or claims. A Ring-LWR commitment opens to every message with probability one. One ciphertext reveals two middle-product encryption rows. A lattice e-voting protocol loses receipt-freeness. A permutation-recovery attack against updatable encryption extends by linear algebra to the old decryption key. An explicit normal basis splits a degree-63 instance into seven degree-nine instances. A signature hash outside the lattice setting maps two printable equal-length messages to the same digest. A rerandomisable scheme's accept bit is a threshold oracle on its decryption noise. Separately, a group-ring decision claim and a multivariate MinRank hardening fail at the assumption or accounting level rather than as complete construction breaks. Each failure occurs one level above its supporting assumption.\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/ai-grinding-for-fun-and-cryptanalysis", "canonical_source": "https://arxiv.org/abs/2608.21986", "published_at": "2026-08-25 18:28:55+00:00", "updated_at": "2026-08-25 18:45:35.014916+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-agents", "ai-research"], "entities": ["arXiv", "Ring-LWR", "middle-product encryption", "lattice e-voting", "updatable encryption", "MinRank"], "alternates": {"html": "https://wpnews.pro/news/ai-grinding-for-fun-and-cryptanalysis", "markdown": "https://wpnews.pro/news/ai-grinding-for-fun-and-cryptanalysis.md", "text": "https://wpnews.pro/news/ai-grinding-for-fun-and-cryptanalysis.txt", "jsonld": "https://wpnews.pro/news/ai-grinding-for-fun-and-cryptanalysis.jsonld"}}