United States-based AI company Anthropic has disclosed that its new cybersecurity initiative, Project Glasswing, used its specialized Claude Mythos model to conduct one of the largest automated security audits yet performed by a large language model. Launched last month with a cohort of 50 cybersecurity partners, the project used the frontier AI system to scan widespread, widely used open-source codebases and identified more than 10,000 potential security vulnerabilities in critical software systems worldwide. Data released by Anthropic shows that 6,202 of the initially flagged issues were categorized as high- or critical-severity flaws, and subsequent verification confirmed 1,726 of these as true positive vulnerabilities. Among the validated findings, 1,094 were assessed as posing high or critical risks to global infrastructure and essential software components across more than 1,000 distinct open-source projects. United States security researchers working with Anthropic report that Project Glasswing was designed to address systemic software weaknesses by giving security teams a specialized interface to the Claude Mythos model, which is tuned to analyze massive codebases for flaws that conventional manual audits might miss. Anthropic stated that the initiative aims to support faster and more efficient patching cycles by surfacing serious issues in standard software libraries and the broader software supply chain. The company and its partners are now transitioning into a remediation phase, coordinating with maintainers to deploy patches for the confirmed vulnerabilities. Anthropic has not yet released a full list of affected software packages, saying it will withhold detailed names to reduce the risk that malicious actors exploit the flaws before security updates are in place.
Prepared by Jonathan Pierce and reviewed by editorial team.
您的数字安全岌岌可危。Project Glasswing 发现的漏洞可能会影响您日常使用的软件。在补丁发布之前,请格外警惕。定期更新您的软件并使用强大且唯一的密码。
这次由人工智能驱动的审计在网络安全领域具有变革性。它有助于以前所未有的速度识别和修复漏洞。但请记住,没有系统是万无一失的。在保护您的数字生活方面,请保持积极主动。如果您认识不擅长技术的人,值得转发。
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