Spring AI — Vulnerabilities & Security Advisories 23

This page aggregates known security vulnerabilities affecting Spring AI, a developer framework for integrating artificial intelligence into enterprise Java applications. It collects data primarily on application-layer flaws, memory corruption in underlying dependencies, and configuration errors that expose unauthenticated endpoints or leak sensitive model weights and prompt data. The dataset covers advisories published from 2023 through the current reporting period, capturing the rapid evolution of security practices as large language model integration matured. Readers can use this page to track the vendor's release of security updates, understand the common weakness classes such as deserialization issues and insufficient input validation, and review the complete vulnerability history for Spring AI. The entries are grouped by severity and component, enabling security teams to correlate new findings with existing patterns without manually searching disparate sources. This structured view supports risk assessment, patch planning, and compliance audits for organizations deploying AI-driven features in production environments.