QoreChain Validates Post-Quantum Crypto With 1,000 QOR Transfer

On July 2, 2026, QoreChain completed a transfer of 1,000 QOR, claiming it is the first fully post-quantum transaction on a live public blockchain mainnet, a transfer now independently verifiable on a public block explorer. Unlike many projects that address only single cryptographic components, QoreChain secured the transaction end-to-end using all three NIST-standardized post-quantum algorithms: ML-DSA-87, ML-KEM-1024, and SHAKE-256. The receiving wallet, created within the Keplr application, demonstrates compatibility with existing crypto infrastructure, potentially easing adoption for users. “Being first is not the point; being ready is,” said Tilak Patel, President and CEO of QoreChain, emphasizing the need for standardized, live, and verifiable post-quantum security as the threat of “Harvest Now, Decrypt Later” attacks looms for unencrypted blockchain data.

QoreChain Completes First End-to-End Post-Quantum Blockchain Transaction

Unlike many projects making similar claims, QoreChain highlights that its transaction employed post-quantum cryptography across the entire cryptographic pathway, not merely replacing a single element vulnerable to future quantum computers. Specifically, the transfer utilized three algorithms standardized by the United States National Institute of Standards and Technology: ML-DSA-87, ML-KEM-1024, and SHAKE-256, for signing, key exchange, and hashing respectively. This comprehensive approach, the company argues, is crucial for genuine long-term security in a post-quantum world. Liviu Epure, Founder and CTO of QoreChain, explained that for years, the company faced skepticism regarding the timing of this technology, stating, “For years, the response to our thesis was that it was too early.” He emphasized this demonstration moves beyond theoretical discussions, noting this isn’t a limited, experimental setup, but a fully functional transaction accessible through standard tools.

This accessibility is a key component of QoreChain’s strategy, as the company aims to deliver post-quantum security without disrupting established user workflows. The timing of this achievement is particularly relevant given the growing awareness of a tactic known as “Harvest Now, Decrypt Later.” Security researchers have documented this strategy, where encrypted data is collected and stored with the intention of decrypting it once sufficiently powerful quantum computers become available. Because blockchains permanently and publicly record transaction history, QoreChain argues that any ledger not secured with post-quantum cryptography from its inception risks retroactive exposure. Tilak Patel also stated, “Being first is not the point.” The transaction itself is publicly verifiable on the QoreChain explorer, inviting scrutiny from the cryptographic community.

Being first is not the point. Being ready is.

Tilak Patel, President and CEO, QoreChain Association

Disclaimer. This article is for informational purposes only and does not constitute investment, financial or professional advice. Quantum computing and the cryptography that secures digital assets both evolve rapidly and information may become outdated. Always conduct your own research and consult qualified advisers before making investment decisions. Digital assets are highly volatile and involve significant risk, including the potential loss of your entire investment, and past performance is not indicative of future results.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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