Coinbase has fully rolled out its integration with the Solana blockchain, enabling users to trade millions of Solana-based tokens directly within the Coinbase app via its built-in decentralized exchange (DEX) functionality.
This doesn’t require official centralized listings on Coinbase’s exchange—instead, it leverages Solana’s leading DEX aggregator, Jupiter, to handle routing and execution across various Solana DEXs for seamless swaps. Tokens become tradable almost immediately after launching on Solana (or Base), with no extra setup needed for projects.
The integration expands access to a massive number of tokens often cited in the millions and taps into Solana’s high-speed, low-cost ecosystem. It’s live for users in supported regions like the US excluding New York in some reports and Brazil, with phased global rollout.
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Coinbase CEO Brian Armstrong highlighted the completion reaching “100%”, emphasizing faster trading, broader token access, and improved user experience. This move positions Coinbase more as an “everything app” for crypto, bridging custodial services with on-chain DeFi trading and boosting Solana’s visibility among mainstream users.
Coinbase Releases Post-Quantum Roadmap
Coinbase has outlined and is actively advancing a comprehensive post-quantum security roadmap to prepare for potential threats from quantum computing, which could eventually break current cryptographic algorithms used in blockchains.
A major recent step includes establishing an independent Advisory Board on Quantum Computing and Blockchain, featuring experts from academia and industry like affiliations with Stanford and UT Austin. The board will: Assess quantum risks to blockchain systems.
Publish position papers and security recommendations. Support real-time responses to quantum advances. The first position paper on quantum risk assessment and a resilience roadmap is expected early in 2026.
Broader elements of the roadmap include: Immediate product enhancements, such as updates to Bitcoin address handling to improve quantum resistance. Long-term cryptographic research, focusing on adopting post-quantum signature schemes e.g., lattice-based like ML-DSA.
Ongoing efforts to mitigate risks to assets like Bitcoin without hype-driven panic. This proactive stance addresses growing concerns in the crypto space about quantum threats, aiming to future-proof user funds and infrastructure.
Coinbase has also released related research insights on the quantum threat to Bitcoin and mitigation strategies. ML-DSA (Module-Lattice-Based Digital Signature Algorithm) is the standardized name for what was originally known as CRYSTALS-Dilithium.
It is a post-quantum digital signature scheme selected and finalized by NIST in FIPS 204. It provides strong security against both classical and quantum attacks, based on the hardness of lattice problems — specifically, the Module Learning With Errors (MLWE) problem and a variant called SelfTargetMSIS (a nonstandard Module Short Integer Solution problem).
ML-DSA operates over the polynomial ring Rq=Zq[X]/(X256+1)R_q = \mathbb{Z}_q[X] / (X^{256} + 1)R_q = \mathbb{Z}_q[X] / (X^{256} + 1), where q=8380417q = 8380417q = 8380417 (a prime), and uses the Number Theoretic Transform (NTT) for efficient polynomial multiplication.
All coefficients are integers modulo ( q ), and the scheme employs rejection sampling, hint-based compression, and pseudorandom expansion from seeds via SHAKE-256 XOF. Parameter SetsML-DSA defines three parameter sets, each targeting different NIST security strength categories roughly corresponding to classical security bits and quantum resistance.
These parameters balance security, key/signature sizes, and performance (higher parameters increase sizes but provide more security margin). Signatures are larger than classical schemes like ECDSA (64–72 bytes) or Ed25519 (64 bytes), but signing and verification are efficient (often comparable or faster in optimized implementations, especially with AVX2).
Signing (Sign); Uses Fiat-Shamir with aborts (rejection sampling) for zero-knowledge:Derive message hash ? = H(H(pk) || M). Derive per-signature randomness ?” from K, randomness, ?. Loop (rejection sampling): Sample masking y ? [-??+1, ??]^? from ?”. Compute w = A y ? decompose to high bits w?. Hash ? || Encode(w?) ? challenge polynomial c (sparse, exactly ? ±1 coeffs via SampleInBall). Compute response z = y + c s?. Check bounds: ?z?_? < ?? – ?, low bits of w – c s? within bounds, hint h = MakeHint(…) has ? ? 1’s. If any fail ? retry with new ?. Signature ? = Encode(Encode(c) || z mod ±q || h).
Provable security in the quantum random oracle model (EUF-CMA / SUF-CMA). Hedged signing using fresh randomness is recommended to resist side-channels; deterministic mode exists but is riskier.
ML-DSA is designed as a direct drop-in replacement for ECDSA/EdDSA/RSA signatures in protocols needing quantum resistance, though larger sizes require protocol adjustments (e.g., in TLS, certificates). For the full formal spec, algorithms, and proofs, refer to NIST FIPS 204.