Claude가 25년 된 암호 미스터리를 풀었다—하지만 비트코인은 안전하다

Anthropic says an internal Claude research model traced the unexplained seeds behind several NIST elliptic curves to outputs from the C library function lrand48, initialized with Unix timestamps from 1997 and 1998. The finding addresses a long-running provenance mystery. It does not break elliptic-curve cryptography, reveal private keys, or create a new threat to Bitcoin.

That distinction is essential because “AI solves cryptographic mystery” can easily become “AI cracks encryption.” The research reconstructs how public curve parameters may have been generated. It does not provide an efficient attack against the discrete-logarithm problem protecting signatures.

What the mystery was

NIST standardized a family of elliptic curves commonly labeled P-192, P-224, P-256, P-384, and P-521. Their construction included seed values intended to show that curve coefficients were generated through a prescribed process rather than deliberately chosen to hide a weakness.

For years, researchers could verify that the published seeds produced the published parameters, yet the origin of those seeds remained unclear. The unexplained inputs fueled suspicion because the curves were developed with involvement from the US National Security Agency, and cryptography had already seen standards undermined by questionable constants.

Provenance matters even when no vulnerability is visible. If parameter choices cannot be explained, users must trust that no party searched secretly for a rare curve with a hidden advantage.

What Claude found

According to Anthropic, the model explored candidate historical random-number generators and initialization methods. It connected the seeds to lrand48, a longstanding pseudo-random generator in C libraries, seeded from plausible Unix timestamps around the period when the curves were created.

The matching process reportedly narrowed a huge search space by combining source-code archaeology, knowledge of historical systems, and computational experiments. The result offers a mundane explanation: engineers may have generated the values with ordinary tools and time-based seeds rather than choosing them to encode a secret trapdoor.

The finding should still be independently reproduced. Anthropic is the primary publisher, and outside cryptographers need to check the timestamp ranges, implementation details, and exact relationship for every curve.

Why this does not break the curves

An elliptic curve’s seed is used to derive public domain parameters. Knowing or reconstructing that seed does not reveal users’ private signing keys. It also does not reverse signatures or make the underlying discrete-logarithm problem easy.

Anthropic explicitly says no user action is required. The research did not identify a backdoor or a practical cryptanalytic weakness in the NIST curves.

The security discussion is about confidence in parameter selection. A transparent generation story reduces one category of suspicion, but it is not a fresh mathematical proof of every implementation’s security. Systems can still fail through weak random keys, side channels, reused nonces, bad libraries, or compromised endpoints.

Why Bitcoin is not affected

Bitcoin does not use NIST P-256 for its core signatures. It uses secp256k1, a different curve with parameters defined by the Standards for Efficient Cryptography group. The newly traced NIST seeds therefore do not change Bitcoin’s signature security.

Even if the story involved the same curve, identifying a parameter-generation seed would not automatically expose wallet keys. Breaking Bitcoin would require a practical attack against secp256k1, a catastrophic implementation flaw, or compromised key handling—not historical provenance for another curve family.

The “Bitcoin is safe” line is therefore not reassurance based on hope. It follows from both the nature of the discovery and the fact that Bitcoin relies on a different curve.

What AI contributed

This work illustrates a valuable use for research agents: connecting scattered historical clues, generating hypotheses, testing code, and searching parameter spaces. The output is useful because its claim can be reproduced with deterministic computations rather than accepted on the model’s authority.

The same approach could help audit legacy standards, trace unexplained constants, reconstruct old software behavior, and prioritize questions for human cryptographers. It is less a magical codebreaker than a tireless research assistant with access to executable tests.

Verdict

Claude appears to have supplied a credible origin story for constants that had remained opaque for roughly a quarter century. If independently confirmed, the result improves transparency around a widely deployed standard and weakens one source of backdoor speculation.

It does not mean encryption has fallen. No private keys were recovered, no NIST curve was shown to be weak, and Bitcoin’s secp256k1 is outside the finding. The breakthrough is historical and methodological: AI helped turn an old question into a reproducible hypothesis.