Using ChatGPT for authorization logic presents significant challenges, primarily due to its inherent lack of determinism and predictability. Authorization requires absolute accuracy and consistency, which LLMs cannot guarantee, potentially leading to unauthorized access or legitimate user lockouts. Security vulnerabilities like prompt injection pose a severe risk, allowing malicious actors to manipulate decisions, while the black-box nature complicates auditing and debugging critical access grants or denials. Furthermore, the latency of LLM inference can severely impact performance for real-time authorization checks, and the associated API costs can quickly become prohibitive in high-volume production environments. Ensuring explainability and compliance becomes nearly impossible without clear insight into why a particular authorization decision was made, making it unsuitable for such a foundational security component. More details: https://m.shopindenver.com/redirect.aspx?url=https://www.abcname.com.ua/