As companies rush to adopt Large Language Models (LLMs), security often takes a backseat. However, the unique nature of LLMs introduces new attack vectors that traditional security measures may not cover.
Prompt Injection
One of the most common vulnerabilities is prompt injection, where an attacker manipulates the model's input to override its instructions. Defending against this requires a multi-layered approach, including input sanitization and robust system prompts.
Data Privacy
Ensuring that sensitive corporate data doesn't leak into public models is paramount. We recommend using private instances of models or enterprise-grade APIs that guarantee data privacy.