Rethinking vulnerability management in the age of AI and CI/CD (blog.apnic.net)

The rise of "vibe coding," where developers direct AI agents to construct software instead of writing it manually, is revolutionizing how vulnerabilities are managed in software development, particularly within CI/CD pipelines. This shift enhances productivity and introduces new methods for identifying and remediating vulnerabilities. When a developer flags a vulnerability, AI can efficiently scan the entire codebase, addressing not just the flagged issue but potentially uncovering and resolving other latent vulnerabilities as the code is rebuilt. This prompts a fundamental re-evaluation of the Common Vulnerabilities and Exposures (CVE) system, traditionally used for tracking vulnerabilities, as older software becomes deprecated in favor of more secure, AI-enhanced solutions. As software evolves at an accelerated pace, the relevance of existing CVEs must be reconsidered. If vulnerabilities are effectively patched within a CI/CD model and no affected versions are in use, the ongoing utility of these CVEs as live threat signals may diminish, relegating them to historical records. Furthermore, the Common Vulnerability Scoring System (CVSS) may require adaptation to better account for operational contexts, highlighting that vulnerabilities can have different implications based on the deployment environment. With the rapid adoption of safer programming languages and architectural practices driven by AI, the landscape of software security is shifting, compelling the industry to rethink its vulnerability management strategies and tools accordingly.