Bitcoin firms press AI labs for pre-release access to frontier models to harden crypto security

The loudest security ask in crypto right now isn’t for more money—it’s for earlier access. More than 40 bitcoin and digital asset companies, including Coinbase, Block, and BitGo, have urged leading AI labs to let independent security researchers work with their strongest models before public launch. The appeal, published Aug. 10 and organized by the Bitcoin Policy Institute with signatories like Blockstream and ARK Invest, targets a practical asymmetry that practitioners feel every day.

Bitcoin alone secures over $1 trillion in value. Surrounding it, wallets, signing devices, libraries, and custody systems collectively safeguard several trillions more. That stack is open-source by design; transparency is a feature, not a bug. But one overlooked edge case in a wallet parser or a node implementation can still vaporize savings. Defenders trying to proactively break and fix that code often run into a constraint: public AI models lock down vulnerability research via guardrails, while vetted early-access programs at frontier labs frequently exclude the maintainers who actually ship the patches.

So maintainers lean on open-weight models they can self-host. Useful, yes—but generally a step behind bleeding-edge capabilities. Meanwhile, attackers abusing jailbroken interfaces, leaked checkpoints, or bespoke inference pipelines don’t wait for permission. That’s the gap the letter aims to close: give qualified defenders earlier access and reasonable compute so they can spot and remediate issues before losses occur, and do it as a standing, trusted-access program for open-source financial infrastructure.

There’s a second time lag that matters. Labs and a small circle of partners typically see new offensive techniques months ahead of the broader ecosystem. Those capabilities tend to diffuse anyway—through public releases, papers, and sometimes compromised systems. If offense leaks by default, the argument goes, defense shouldn’t be the last to know.

This push sits alongside, not instead of, capital commitments. Late last month, the Bitcoin Security Consortium—BlackRock, Coinbase, Strategy, Anchorage, ARK, Block, Blockstream, Fidelity Digital Assets, and Galaxy—pledged $15 million toward the network’s long-term security. The new request targets a narrower choke point: today’s models for the people patching today’s code.

AI companies haven’t staked out a public position on this specific proposal. They are, however, investing in broader safeguards intended to blunt malicious use across domains, whether that’s blockchain coding or something unrelated. That caution isn’t hypothetical. Anthropic has shown how the same underlying systems can enable “vibe hacking,” where criminals use real-time AI assistance to run Bitcoin ransom schemes—lowering the cost of offense.

The hard part isn’t the principle; it’s the implementation. Who qualifies as a “trusted” defender, and how do labs prevent model or capability leakage?

A workable path likely blends controls rather than relying on a single gate: - Tiered access tied to contributor reputation in critical repos (wallets, nodes, key management), with rotating audits and revocation hooks. - Hardware-bound inference and signed session logs so any misuse is attributable and sanctionable. - Sandboxed red-team environments with exploit-hunting tools enabled but explicit egress limits. - Time-boxed previews of new capabilities with compute quotas sized for fuzzing and formal verification workflows, not unlimited exploration. - Clear incident disclosure protocols aligned with open-source norms, plus legal safe harbors for good-faith research.

Designing that stack won’t eliminate risk, but it can shift incentives. Today, many white hats spend cycles reverse-engineering guardrails or settling for weaker models. Give them sanctioned access, and you redirect effort toward preemptive hardening of the code that actually moves funds.

This is less a philosophical debate than an operational one. If defense is going to keep pace with fast-improving generative models, earlier access and targeted compute to the people maintaining wallets and nodes seems like a reasonable trade—especially in a system where transparency is intentional and the attack surface is wide.