
anthropic.com
October 16, 2026
12 min read
69/100
Summary
Anthropic says Claude identified how the unexplained seed values behind major NIST elliptic-curve cryptography standards were generated. In under half an hour in October 2026, an internal research model determined that seeds for NIST P-192, P-224, P-256, P-384 and P-521 were outputs of the legacy C-library lrand48 pseudorandom-number generator initialized with Unix timestamps, rather than hashes of secret phrases or other cryptographic algorithms. NIST adopted these curves in 2000 for the FIPS 186-2 Digital Signature Standard, while the NSA had supplied their seed values without explaining their provenance. Anthropic reconstructed timestamps from May 1997 through April 1998 and the candidate positions that reproduce ten prime-curve and binary-curve seeds; P-256, for example, was the 1,842nd 20-byte candidate from its run. Anthropic says the result is not a cryptographic break or a newly discovered weakness, and that the simple reproducible process makes intentional backdoors less plausible. Claude also traced base points for P-192 and five ANSI X9.62 example curves to the FreeLIP random-number generator, but could not explain base points for P-224, P-256, P-384, P-521 or NIST binary curves. B-163 remains unexplained. Anthropic will donate the $36,864 NIST elliptic-curve seeds bounty to the Internet Security Research Group.
Key Takeaways
What the discussion said
Commenters were impressed that Claude turned a small structural clue in decades-old NIST elliptic-curve seeds into a concrete reconstruction: the values appear to come from a commonplace C random-number generator initialized from timestamps, not the mysterious hash process many had assumed. For many, the striking part was not that AI broke cryptography, but that it closed a long-running provenance puzzle cheaply and quickly enough to puncture a generation of curve-backdoor speculation. Readers also stressed that reconstructing the generation process is not the same as proving every discarded candidate was benign, though the limited timestamp search space makes a deliberately planted, exclusive exploit look implausible. The sharper AI debate was over who gets to use capabilities like this. Several commenters see safety gates and privileged access as a growing divide: labs and approved partners may investigate sensitive security or biology questions while independent researchers and tiny startups hit refusals. Others pushed back that this exact investigation was available to ordinary Claude users, and argued that verified security research is precisely the kind of work providers have incentives to support. A smaller thread questioned how credit should work when a model synthesizes insights absorbed from an untraceable mass of prior research; the response was that human scholarship works similarly, while the demonstrated solution remains a meaningful contribution.
Where opinion split
The central dispute is whether frontier-model safeguards create an unacceptable research moat. Critics argue that providers can reserve powerful dual-use investigation for themselves and state-aligned partners, leaving public-interest researchers unable to test dangerous systems; defenders say Claude was not blocked on this task and that responsible, authenticated security access can enable disclosure without opening abuse channels.
Community Sentiment
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