Entries Tagged "cryptanalysis"

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Measuring Human Cryptanalysis Effort

Matthew Green has a new site that tries to estimate the number of cryptanalyst-hours that have been spent analyzing different public-key algorithms:

Abstract: We estimate how much public cryptanalysis each public-key assumption has received, using the literature itself as the instrument. From roughly sixteen thousand candidate papers we classify cryptanalytic work on ECDLP, structured and plain lattices, syndrome decoding and their comparators, then convert papers into estimated research-allocation years through a person-level author map. These publication-based estimates may substantially overstate actual time spent. Lattices have overtaken elliptic curves in this cumulative measure only recently; we express that history as inference budgets under stated productivity assumptions. The study was conducted by AI models: Claude Fable 5.1 and Claude Opus 5.5 built the pipeline, ran the analysis and wrote this page, with contributions from GPT-6 Astra. Matthew Green set the questions, made the key methodological decisions and oversaw the work.

There are a lot of caveats to this analysis. It relies on published work, so anything unpublished does not count. This includes both academic cryptanalysis that didn’t result in a paper, and intelligence agency cryptanalysis done in secret. But it’s a good first stab at a metric of this sort.

Posted on October 15, 2026 at 12:24 PM • View Comments

GPT-6 Astra Breaks an Old Enigma Message

This is pretty amazing:

However, the most astonishing thing about this break is that the GPT­6 Astra did it entirely on its own. Carter Leffer only directed GPT­6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page. After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX, might be related to the plaintext of the unbroken MVUEH message. After trying many different approaches, GPT­6 Astra focused on using the repeated place name ROSENOW ROSENOW as a crib. After developing the necessary Python and C++ software for an Enigma simulator and an Enigma Bombe, GPT­6 Astra started a thorough break with the ROSENOW crib, which in the end resulted in the correct key and plaintext for the MVUEH message being found.

We are still analysing the GPT­6 Astra logs to see exactly how it executed the break. And we are discovering amazing details.

More details at the link.

Posted on September 22, 2026 at 7:02 AM • View Comments

Measuring LLMs’ Ability to Perform Cryptanalysis

There’s new benchmark measuring AI’s ability to perform mathematical cryptanalysis. Anthropic’s frontier model actually found new attacks.

The benchmark: “CryptanalysisBench: Can LLMs do Cryptanalysis?” The idea is to benchmark the ability of LLMs to discover new mathematical cryptanalytic attacks against a series of historical algorithms.

Abstract: Cryptanalysis—the task of finding attacks against cryptographic schemes—its at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest. Cryptanalysis represents both a clean testbed for frontier reasoning (as practical attacks can be automatically verified) and a domain with unusually high stakes, since the primitives under study underpin our digital security. In this paper we ask whether LLMs can do cryptanalysis, and find that the answer is increasingly yes. We introduce CryptanalysisBench, 191 tasks across six families of cryptographic primitives (block ciphers, hash functions, etc.) drawn primarily from four NIST standardization competitions. Our benchmark consists of three tiers: (i) primitives with known practical breaks; (ii) primitives with no known practical break, evaluated both at full strength and as scaled-down variants; and (iii) a challenge set of production primitives at the frontier of cryptanalysis. Five frontier models (Claude Opus 4.8, Sonnet 5, Mythos 5, GPT-5.5, and the open-weights GLM-5.2) break 65%­86% of Tier 1 schemes, 6­12 Tier-2 schemes at full strength, and 24­61 across all scaled-down variants. Beyond deriving known results, models produce novel cryptanalysis, such as a key-recovery attack that exploits a design flaw in the SpoC AEAD and an error in KINDI’s published CCA-security proof, both to the best of our knowledge not previously known.

We release CryptanalysisBench as a tool to help track if (or when) AI cryptanalysis becomes a serious factor and as a scaffold for stress-testing candidate schemes before deployment. The attacks that the benchmark already surfaces are an early snapshot of a fast-moving frontier that may soon match, and in places exceed, the published state of the art.

Anthropic used the benchmark to test Mythos Preview, and found new vulnerabilities in Hawk and reduced-round AES.

Still early results, but this is definitely something to watch.

SlashDot thread.

Posted on July 28, 2026 at 9:47 PM • View Comments

New Cryptanalysis of the Fiat-Shamir Protocol

A couple of months ago, a new paper demonstrated some new attacks against the Fiat-Shamir transformation. Quanta published a good article that explains the results.

This is a pretty exciting paper from a theoretical perspective, but I don’t see it leading to any practical real-world cryptanalysis. The fact that there are some weird circumstances that result in Fiat-Shamir insecurities isn’t new—many dozens of papers have been published about it since 1986. What this new result does is extend this known problem to slightly less weird (but still highly contrived) situations. But it’s a completely different matter to extend these sorts of attacks to “natural” situations.

What this result does, though, is make it impossible to provide general proofs of security for Fiat-Shamir. It is the most interesting result in this research area, and demonstrates that we are still far away from fully understanding what is the exact security guarantee provided by the Fiat-Shamir transform.

Posted on September 9, 2025 at 7:02 AM • View Comments

1965 Cryptanalysis Training Workbook Released by the NSA

In the early 1960s, National Security Agency cryptanalyst and cryptanalysis instructor Lambros D. Callimahos coined the term “Stethoscope” to describe a diagnostic computer program used to unravel the internal structure of pre-computer ciphertexts. The term appears in the newly declassified September 1965 document Cryptanalytic Diagnosis with the Aid of a Computer, which compiled 147 listings from this tool for Callimahos’s course, CA-400: NSA Intensive Study Program in General Cryptanalysis.

The listings in the report are printouts from the Stethoscope program, run on the NSA’s Bogart computer, showing statistical and structural data extracted from encrypted messages, but the encrypted messages themselves are not included. They were used in NSA training programs to teach analysts how to interpret ciphertext behavior without seeing the original message.

The listings include elements such as frequency tables, index of coincidence, periodicity tests, bigram/trigram analysis, and columnar and transposition clues. The idea is to give the analyst some clues as to what language is being encoded, what type of cipher system is used, and potential ways to reconstruct plaintext within it.

Bogart was a special-purpose electronic computer tailored specifically for cryptanalytic tasks, such as statistical analysis of cipher texts, pattern recognition, and diagnostic testing, but not decryption per se.

Listings like these were revolutionary. Before computers, cryptanalysts did this type of work manually, painstakingly counting letters and testing hypotheses. Stethoscope automated the grunt work, allowing analysts to focus on interpretation, and cryptanalytical strategy.

These listings were part of the Intensive Study Program in General Cryptanalysis at NSA. Students were trained to interpret listings without seeing the original ciphertext, a method that sharpened their analytical intuitive skills.

Also mentioned in the report is Rob Roy, another NSA diagnostic tool focused on different cryptanalytic tasks, but also producing frequency counts, coincidence indices, and periodicity tests. NSA had a tradition of giving codebreaking tools colorful names—for example, DUENNA, SUPERSCRITCHER, MADAME X, HARVEST, and COPPERHEAD.

Posted on September 2, 2025 at 7:08 AM • View Comments

The NSA’s “Fifty Years of Mathematical Cryptanalysis (1937–1987)”

In response to a FOIA request, the NSA released “Fifty Years of Mathematical Cryptanalysis (1937-1987),” by Glenn F. Stahly, with a lot of redactions.

Weirdly, this is the second time the NSA has declassified the document. John Young got a copy in 2019. This one has a few less redactions. And nothing that was provided in 2019 was redacted here.

If you find anything interesting in the document, please tell us about it in the comments.

Posted on May 19, 2025 at 7:06 AM • View Comments

Improvements in Brute Force Attacks

New paper: “GPU Assisted Brute Force Cryptanalysis of GPRS, GSM, RFID, and TETRA: Brute Force Cryptanalysis of KASUMI, SPECK, and TEA3.”

Abstract: Key lengths in symmetric cryptography are determined with respect to the brute force attacks with current technology. While nowadays at least 128-bit keys are recommended, there are many standards and real-world applications that use shorter keys. In order to estimate the actual threat imposed by using those short keys, precise estimates for attacks are crucial.

In this work we provide optimized implementations of several widely used algorithms on GPUs, leading to interesting insights on the cost of brute force attacks on several real-word applications.

In particular, we optimize KASUMI (used in GPRS/GSM),SPECK (used in RFID communication), andTEA3 (used in TETRA). Our best optimizations allow us to try 235.72, 236.72, and 234.71 keys per second on a single RTX 4090 GPU. Those results improve upon previous results significantly, e.g. our KASUMI implementation is more than 15 times faster than the optimizations given in the CRYPTO’24 paper [ACC+24] improving the main results of that paper by the same factor.

With these optimizations, in order to break GPRS/GSM, RFID, and TETRA communications in a year, one needs around 11.22 billion, and 1.36 million RTX 4090GPUs, respectively.

For KASUMI, the time-memory trade-off attacks of [ACC+24] can be performed with142 RTX 4090 GPUs instead of 2400 RTX 3090 GPUs or, when the same amount of GPUs are used, their table creation time can be reduced to 20.6 days from 348 days,crucial improvements for real world cryptanalytic tasks.

Attacks always get better; they never get worse. None of these is practical yet, and they might never be. But there are certainly more optimizations to come.

EDITED TO ADD (4/14): One of the paper’s authors responds.

Posted on March 17, 2025 at 11:09 AM • View Comments

Implementing Cryptography in AI Systems

Interesting research: “How to Securely Implement Cryptography in Deep Neural Networks.”

Abstract: The wide adoption of deep neural networks (DNNs) raises the question of how can we equip them with a desired cryptographic functionality (e.g, to decrypt an encrypted input, to verify that this input is authorized, or to hide a secure watermark in the output). The problem is that cryptographic primitives are typically designed to run on digital computers that use Boolean gates to map sequences of bits to sequences of bits, whereas DNNs are a special type of analog computer that uses linear mappings and ReLUs to map vectors of real numbers to vectors of real numbers. This discrepancy between the discrete and continuous computational models raises the question of what is the best way to implement standard cryptographic primitives as DNNs, and whether DNN implementations of secure cryptosystems remain secure in the new setting, in which an attacker can ask the DNN to process a message whose “bits” are arbitrary real numbers.

In this paper we lay the foundations of this new theory, defining the meaning of correctness and security for implementations of cryptographic primitives as ReLU-based DNNs. We then show that the natural implementations of block ciphers as DNNs can be broken in linear time by using such nonstandard inputs. We tested our attack in the case of full round AES-128, and had success rate in finding randomly chosen keys. Finally, we develop a new method for implementing any desired cryptographic functionality as a standard ReLU-based DNN in a provably secure and correct way. Our protective technique has very low overhead (a constant number of additional layers and a linear number of additional neurons), and is completely practical.

Posted on February 21, 2025 at 10:33 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.