AI and open source security: Reducing the response gap for Common Vulnerabilities and Exposures (CVE) exposure

This post details how AI is accelerating vulnerability discovery and exploitation, compressing the window between a defect's existence and its operationalization. It highlights the increasing effectiveness of AI in identifying and assessing vulnerabilities, leading to a shrinking response gap for CVEs. The post also emphasizes the importance of maintaining dependency inventories, identifying unsupported frameworks, and considering extended support. It uses the Spring ecosystem as an example, noting 14 CVEs disclosed in April 2026, including two critical severity vulnerabilities related to unsafe deserialization and expression evaluation. The post also discusses the increased exposure from end-of-support frameworks and recommends maintaining dependency inventories, identifying unsupported frameworks, prioritizing migration, and ensuring vulnerability coverage. IBM Library Support for Open Source is mentioned as a solution for extended support.