Stephen A. Weis factors RSA-896 with Anthropic Claude assistance
Researcher Stephen A. Weis has factored RSA-896, a 270-decimal-digit semiprime, using Anthropic's Claude AI model. The achievement on September 19, 2026, pushed the public factoring record from 862 bits to 896 bits. This milestone comes just 16 days after Eric Lu of Cognition set the previous record of 862 bits on September 3, 2026, using Devin AI agents.
Key points
- Stephen A. Weis factored the 896-bit RSA-896 semiprime on September 19, 2026, using Anthropic's Claude.
- The achievement broke the previous 862-bit record set just 16 days prior by Eric Lu using Cognition's Devin.
- Both records relied on optimizing the classical general number field sieve algorithm rather than quantum computing.
Both breakthroughs utilized the general number field sieve (GNFS) algorithm rather than quantum computing. The AI models acted as collaborators to optimize the classical approach, helping to navigate complex parameter spaces that typically require months of manual configuration by specialized teams. While Lu's effort consumed about 4,900 GPU-days at an estimated cost of $400,000, the compute cost for Weis's RSA-896 factoring has not been published.
RSA-896 factored with AI assistance, pushing the public record to 896 bits
cryptobriefing.com · 18 September 2026
Photo: Merlin Lightpainting / Pexels
Cryptographers have been chipping away at RSA factoring records for decades, but the pace just got uncomfortably fast. On September 19, 2026, researcher Stephen A. Weis factored RSA-896, a 270-decimal-digit semiprime, with help from Anthropic’s Claude AI model. The achievement moved the public factoring record from 862 bits to 896 bits in 16 days.
To put that timeline in perspective: the previous record had been set on September 3, 2026, by Eric Lu of Cognition, who used the company’s Devin AI agents to factor the 862-bit RSA-260 number. Two researchers, two different AI systems, two records in just over two weeks.
What actually happened here
Both breakthroughs relied on the general number field sieve, or GNFS, the classical algorithm that has dominated large-number factoring since the early 1990s. No quantum computing was involved. The AI assistance accelerated and optimized the classical approach rather than replacing it with something exotic.
Lu’s RSA-260 factoring consumed roughly 4,900 GPU-days at an estimated compute cost of $400,000. Weis’s RSA-896 effort has not had its compute cost published, but the 16-day gap between the two records suggests the AI-assisted optimization is meaningfully compressing what used to be multi-year projects.
The RSA Factoring Challenge, which originally sponsored these efforts, ran from 1991 to 2007. The $75,000 prize that once accompanied RSA-896 is long gone. Weis and Lu were chasing records, not prize money.
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Why the RSA challenge numbers matter
RSA encryption works because multiplying two large prime numbers together is easy, but reversing the process, finding those original primes from the product, is extraordinarily hard. The security of RSA-2048, the standard most widely deployed today, depends on that difficulty remaining computationally intractable.
RSA-896 is not RSA-2048. The gap between 896 bits and 2048 bits is not linear. Each additional bit roughly doubles the difficulty, so 2048-bit numbers remain orders of magnitude harder to factor than anything broken so far.
The previous major milestone, RSA-250 at 829 bits, was factored in 2020 using purely classical methods. Going from 829 bits in 2020 to 896 bits in 2026 is a meaningful jump, and the acceleration introduced by AI tooling suggests the curve may steepen further.
What this means for cryptographic infrastructure
For organizations running systems that depend on RSA encryption below 2048 bits, these records are a concrete signal to audit key lengths. Legacy systems, embedded hardware, and older TLS configurations sometimes still use 1024-bit keys, a length that was flagged as insufficient years ago. The RSA-896 result adds urgency to those long-standing recommendations without changing the fundamental security analysis for properly configured modern systems.
Two AI companies, Anthropic and Cognition, now have their models credited on consecutive public factoring records. Both Weis and Lu used AI models as collaborators on technically demanding work that previously required rare, highly specialized expertise. Claude helped Weis navigate the parameter space of a computation that would have taken a small team of number theorists months to configure manually.
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