This research introduces prompt obfuscation techniques to prevent unauthorized extraction of system prompts in large language models, protecting valuable intellectual property.

• Demonstrates that current system prompts are vulnerable to extraction attacks
• Proposes novel obfuscation methods to defend against prompt stealing
• Evaluates effectiveness of these defensive techniques across various attack scenarios
• Highlights the importance of balancing security with model performance

For security professionals, this research provides practical approaches to safeguard proprietary AI instructions without significantly degrading model utility—a critical advancement as LLMs become more integrated into business operations.

Prompt Obfuscation for Large Language Models