As LLMs become integral to production systems, security is no longer an afterthought. The OWASP LLM 2025 guidelines provide a framework for addressing the top risks, including prompt injection and sensitive information disclosure. This article offers a practical, minimal implementation of these guardrails, showing developers how to intercept malicious prompts and mask sensitive data before it reaches the model. The approach focuses on simplicity and effectiveness, making it accessible for teams with limited security resources. Key techniques include input validation, output filtering, and context-aware redaction. For developers and security engineers, understanding these patterns is essential for building trustworthy AI applications. The article bridges the gap between security standards and real-world implementation, offering a starting point for hardening LLM deployments.
Learn how to implement OWASP LLM 2025 security guardrails, including prompt injection interception and sensitive data masking, with a minimal viable approach.