[Security Team Uses Cutting-Edge AI to Simulate Attacks on 150 Bitcoin Core Projects, Averaging One Critical Vulnerability Found Per Person Per Hour] BlockBeats News, August 9: A volunteer security team recently utilized advanced AI models to scan approximately 150 Bitcoin Core project-related codebases, uncovering more than a dozen vulnerabilities involving wallets, cryptographic libraries, and infrastructure projects. Reportedly, the team employed Kimi K3, OpenAI's GPT Sol, Anthropic's Claude Fable and Opus models, as well as Z.ai's GLM 5.2 to identify vulnerabilities and generate supporting documentation. Team members stated that they are currently able to discover an average of one critical vulnerability per person per hour. Over the past 12 hours, they have submitted security reports to multiple projects, though the specific affected projects have not yet been disclosed. Recent security incidents involving Coldcard and Boltz also demonstrate that AI is being used by both security researchers and attackers to identify software vulnerabilities more quickly. [Original Link]