Spring Boot AI Systems Face Twin Security Threats from Prompt Input

Spring Boot teams integrating LLMs commonly embed confidential business logic or credentials in system prompts, inadvertently exposing them to two distinct attack vectors that share the same user-input channel. Prompt injection overwrites your instructions, while system prompt leakage extracts them—and transformer models provide no cryptographic boundary between system and user messages. Most teams defend against injection but ignore leakage, leaving secrets vulnerable and requiring fundamentally different mitigation strategies for each threat.