RETRIEVE PROMPT THROUGH REVERSE ENGINEERING

Large Language Models (LLMs) handle substantially more complicated natural language processing tasks, although they rely largely on well-crafted prompts for maximum performance. Manual prompt engineering, on the other hand, is time-consuming, frequently suboptimal, and inflexible in the face of multiple input prompt variations. Furthermore, there is an increasing need to address the security implications of prompt-extraction attacks.Existing research has proposed automated methods for prompt engineering, which range from rewriting underoptimized prompts to creating high-quality human-like prompts from scratch. Despite these advances, issues remain in achieving timely efficacy, robustness, and security.