cyber-security vulnerabilities are usually published in form of short natural
language descriptions (e.g., in form of MITRE's CVE list) that over time are
further manually enriched with labels such as those defined by the Common
Vulnerability Scoring System (CVSS). In the Vulnerability
本文介绍了一种基于 Transformer 学习框架的新方法 (V2W-BERT)，通过自然语言处理、链接预测和迁移学习等思想，自动将 Common Vulnerabilities and Exposures (CVE) 映射到 Common Weakness Enumerations (CWE)，准确地解决了在网络安全方面的问题，可应用于寻找软件漏洞和缓解网络攻击。