ME News reports that on August 9 (UTC+8), a voluntary security team recently scanned approximately 150 code repositories related to Bitcoin Core projects using advanced AI models, uncovering over a dozen vulnerabilities across wallets, cryptographic libraries, and infrastructure projects. The team utilized Kimi K3, OpenAI’s GPT Sol, Anthropic’s Claude Fable and Opus models, and Z.ai’s GLM 5.2 to identify vulnerabilities and generate supporting documentation. Team members stated that, on average, each person can now identify about one critical vulnerability 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 further demonstrate that AI is being used simultaneously by security researchers and attackers to rapidly discover software vulnerabilities. (Source: BlockBeats)
The Security Team Uses AI to Detect Critical Vulnerabilities in 150 Bitcoin Core Projects
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Summary
A volunteer security team recently used AI to identify critical vulnerabilities in 150 Bitcoin core-related projects, revealing a significant security breach risk. The team scanned code repositories using models such as Kimi K3, GPT Sol, and GLM 5.2, uncovering more than a dozen flaws in wallets, libraries, and infrastructure. Each team member discovered one critical issue per hour, with reports submitted over the past 12 hours. The affected projects have not been named. This effort represents a key development in AI and crypto news, demonstrating how machine learning can accelerate security audits.
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