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How to Safeguard Large Language Models: Mitigating Prompt Injections and Jailbreaks
Learn how large language models are vulnerable to harmful prompts and unauthorized access. Discover strategies to protect against these threats.
The integration of Large Language Models (LLMs) has propelled language-centric applications to new heights. However, with this advancement comes a surge in security vulnerabilities. Understanding and countering prompt injections and jailbreaks within LLMs is critical for ensuring robust application security. The Deeplearning.AI provide has released an online workshop ‘Navigating LLM Threats: Detecting Prompt Injections and Jailbreaks’. This article is the brief notes for this workshop.
Let’s delve into these threats and explore effective measures to mitigate them.
What is a Prompt Injection?
Prompt injections involve injecting harmful prompts into LLMs, exploiting their language generation capabilities. These injections often constitute OWASP’s top critical issues, enabling adversarial actors to manipulate the system’s responses.
