**American AI Restrictions Push Bitcoin Defenders to Chinese Models**
In a striking turn of events, prominent Bitcoin company leaders and open-source developers are revealing that Chinese AI models are currently outperforming restricted American frontier systems in critical defensive cybersecurity work. Forced by what they describe as crippling limitations from U.S. AI providers, researchers safeguarding vital Bitcoin infrastructure are turning to open-source alternatives from China to identify and patch vulnerabilities before malicious actors can exploit them.
A stark illustration of this shift comes from Rob Hamilton, CEO of AnchorWatch, a Bitcoin self-custody insurance company. After integrating OpenAI’s trusted cyber program—a process which had already been completed through KYC months prior—he was unexpectedly blocked from further analysis on a codebase he had responsibly disclosed. Hamilton expressed deep frustration, stating, “It absolutely guts me as a patriotic American to have to do this, but I will be going back to using Chinese open source models to conduct my research to protect Bitcoin infrastructure.” He elaborated that while “Black hats will not hit these issues. The white hats will,” American models repeatedly blocked his attempts to red-team Bitcoin infrastructure, even after brief access grants.
Francis Pouliot, founder of Bull Bitcoin, a Bitcoin-only exchange focused on self-custody infrastructure, was equally blunt in his assessment. “I have never seen OpenAI this cucked. It’s cucked beyond belief now. Not even for security, for anything related to Bitcoin,” he posted, adding that the “USA AI industry is completely cooked if they don’t change this path.” Pouliot championed open-source Chinese LLMs, like Kimi K3, noting their usefulness. In a detailed follow-up, he described how a Chinese open-source model successfully identified a money-stealing exploit in a project during auditing, demonstrated it on regtest, and assisted in patching it. Conversely, when he asked the American models he paid for to review the same fix, they refused.
The performance gap was also highlighted by PortlandHODL, a Bitcoin Core contributor who builds for AnchorWatch. Summarizing the situation, they posted: “US-based Frontier AI Model – ‘You’re absolutely right!’ Chinese Open Model – ‘78 critical vulnerabilities found.’ The implications of this are unfathomable.” Adding to the urgency, PortlandHODL stated they felt they were “basically asking Xi to not get my software hacked at this point,” and called on OpenAI and Anthropic to create proper access programs for U.S. citizens engaged in defensive security work.
Alex Thorn, Head of Firmwide Research at Galaxy, signed a recent Bitcoin Policy Institute open letter demanding trusted access to frontier models for open-source defenders. Thorn wrote, “Americans should not have to rely on Chinese AI to defend themselves, their projects, companies, or clients from cyber-attacks,” emphasizing that “RED TEAM NEEDS THE MODELS.”
This sentiment was echoed in a broader industry letter published by the Bitcoin Policy Institute on August 10. Co-signed by more than 70 organizations across the digital-asset ecosystem—including major custodians, exchanges, mining firms, and open-source development groups—the letter calls on frontier AI labs to establish clear trusted-access programs for qualified open-source and digital-asset defenders. It argues that current restrictions and safety guardrails leave legitimate security researchers without access to the strongest models, forcing them to rely on less capable open-weight alternatives while sophisticated attackers face no such limits. The signatories request early access to cyber-capable models, sufficient compute resources, secure environments for reviewing code, and direct channels with lab security teams, stating that frontier AI could become one of the most powerful defensive technologies available if defenders are given fair access.
These accounts point to a broad pattern: American models from OpenAI and Anthropic frequently refuse or restrict legitimate defensive work, even for authorized users, while Chinese models such as Kimi K3 operate with greater flexibility and are delivering confirmed results. Concerns about hosting infrastructure for Chinese models as a potential attack vector can be mitigated, proponents argue, since they are open source and can be run on American-hosted data centers—a trend that could further challenge the U.S. AI market if it persists.
### Coldcard Exploit Triggers Ecosystem-Wide Response
The cybersecurity pressure on the community intensified following a firmware flaw in Coldcard hardware wallets that was exploited beginning July 30, resulting in the theft of over $100 million in bitcoin from seeds generated with insufficient entropy. Bitcoin Magazine issued an urgent advisory: “COLDCARD SECURITY RISK: IMMEDIATE ACTION REQUIRED.”
In response, a volunteer effort known as the Bitcoin Red Team formed, led by open-source developer Calle (creator of Cashu and the Android version of Bitchat) and Rob Hamilton. The group has conducted large-scale AI-assisted audits of Bitcoin open-source repositories, using models including Kimi K3 as the primary workhorse alongside limited access to Western systems. Early results, covered by Bitcoin Magazine, revealed thousands of findings across hundreds of projects, including dozens of critical issues, with spending largely covered by OpenSats.
By August 8, after more than 100 hours of work involving dozens of contributors, the team reported scanning 501 projects and producing 7,958 findings, of which 1,280 were rated high or critical severity. The majority of compute spend continued to go to Chinese open-weight models.
### Lessons from the Red Team Campaign
Most recently, Calle shared lessons from the intensive red-team period. The effort has essentially completed a basic scan of virtually the entire Bitcoin open-source landscape; low-hanging fruit is largely exhausted. Maintainers across projects have validated many of the critical and high-severity reports, while response times vary widely and serve as a signal of overall project health.
Key takeaways include the need for every project to maintain its own permanent AI audit pipeline going forward. Projects that began such reviews months earlier are in a markedly stronger position. Unmaintained repositories should be treated as likely broken and unreliable. Calle also warned that the human-only era of open-source security review is over; verification is now effectively free, and information overload must be handled with AI rather than complaints about “PR slop.” Multiple concurrent and diverse human approaches remain the strongest method for finding vulnerabilities, and external red-teaming will likely be required indefinitely. Calle repeatedly emphasized that developers should stop writing security-critical code in C, explaining that memory-safety vulnerabilities which required a highly skilled hacker to exploit in the past can now be triggered with a single prompt.
Bitcoin was the first major open-source ecosystem to confront this collision between accumulated human code and frontier AI capability, and the rest of the software world is expected to follow.
### FAQ
**Why are Bitcoin researchers turning to Chinese AI models?**
Bitcoin researchers are turning to Chinese AI models because U.S. frontier models, such as those from OpenAI and Anthropic, frequently refuse or restrict legitimate defensive cybersecurity work. Restrictions block access even for authorized users conducting responsible audits. In contrast, Chinese open-source models like Kimi K3 operate without stringent guardrails, allowing researchers to identify critical vulnerabilities in Bitcoin infrastructure codebases effectively.
**What specific issues have been reported with U.S. AI models?**
Users have reported being blocked from analysis on codebases they were authorized to review, denied access to models they had previously used, and refused assistance when auditing patches for security exploits, even after completing necessary onboarding procedures like KYC. These restrictions have forced researchers to seek alternative tools to secure critical systems.
**What is the Bitcoin Red Team and what has it accomplished?**
The Bitcoin Red Team is a volunteer-led cybersecurity initiative formed in response to the Coldcard wallet exploit. Led by developers like Calle and Rob Hamilton, the team uses AI-assisted audits, primarily with Chinese open-source models, to review Bitcoin open-source repositories. By August 8, they had scanned over 500 projects, identifying nearly 8,000 findings, including more than 1,280 high or critical severity vulnerabilities.
**Are there concerns about using Chinese AI models?**
While there are concerns about potential attack vectors related to hosting foreign AI infrastructure, proponents note that these models are open source and can be run on American-hosted data centers. This mitigates some risks and provides a transparent, auditable security process, unlike the opaque restrictions imposed by some U.S. providers.
**What recommendations emerged from the Bitcoin Policy Institute open letter?**
The open letter, signed by over 70 organizations, calls on frontier AI labs to establish clear trusted-access programs for qualified open-source and digital-asset defenders. It requests early access to cyber-capable models, sufficient compute resources, secure code review environments, and direct communication channels with lab security teams to enable effective defensive work.
### Conclusion
The growing reliance of Bitcoin security researchers on Chinese AI models highlights a critical gap in U.S. AI policy for cybersecurity. As American frontier systems impose restrictions that hinder defensive efforts, the Bitcoin community has pragmatically turned to open-source alternatives from China to protect vital infrastructure. This shift underscores an urgent need for trusted-access programs and collaborative frameworks that enable legitimate security research without compromising safety. The lessons learned from this cybersecurity campaign will likely influence AI governance far beyond Bitcoin, affecting the broader software ecosystem for years to come.
