Security teams used cutting-edge AI to conduct simulated attacks on 150 core Bitcoin projects, discovering an average of one critical vulnerability per person per hour.
1 hours ago
A volunteer security team recently used cutting-edge AI models to scan roughly 150 codebases related to core Bitcoin projects, discovering over a dozen vulnerabilities spanning wallets, cryptography libraries, and infrastructure projects. According to reports, the team leveraged models including Kimi K3, OpenAI’s GPT Sol, Anthropic’s Claude Fable and Opus, and Z.ai’s GLM 5.2 to identify vulnerabilities and generate supporting documentation. Team members stated each researcher is now finding approximately one critical vulnerability per hour. Over the past 12 hours, the team has submitted security reports to multiple projects, though the specific affected projects have not been disclosed. Recent security incidents involving platforms like Coldcard and Boltz also highlight that AI is being used by both security researchers and malicious actors to discover software vulnerabilities at a faster pace.
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