How to Protect Against AI Prompt Injection Attacks

Now that we have learned about AI prompt injection and how they can affect the reputation of tools, it’s time to know about some defenses and ways to protect against such attacks. There are essentially three ways to do it, so let us learn about each of those in detail:

• Prompt Engineering

Even the most detailed prompts are not reliable as you never know if the AI model will prioritize the more recent prompt. According to the large language model’s POV, both are just prompts and are on equal footing. It needs to be assured that the system follows your prompt instructions without fail and doesn’t get hijacked. Developers have to define strict boundaries that shall never be crossed or bypassed.

• Fine Tuning

Fine-tuning is a great way to control the output generated by AI models. Similar to the way we use coding to add features to a tool, fine-tuning can introduce new functionality to the AI language model tools. Fine-tuning introduces an extra layer of security to such tools. You don’t need to format the prompt just right as fine-tuning the model controls the output and keeps it on track natively. While it might sound difficult or need a lot of effort but is quite easy and also has some platforms that specialize in this process like Entry Point AI. So you can also outsource the fine-tuning process.

• Early Tests

No matter how much effort you put into developing the tool and deploying safeguards, testing is a must. Before deploying and even when the tool is live, you must continue testing it to prevent potential attacks and vulnerabilities. LLM’s are very sensitive to prompts and are prone to errors so testing is the best thing that you can do to avoid such attacks.

With the advancement in technology, hackers around the world have come up with new and innovative ways to take advantage of vulnerabilities posing threat to online tools. By now you must be familiar with ChatGPT and similar language models but did you know these are also vulnerable to attacks?

The answer to that question is a big Yes, despite all the intellectual capabilities it still has some weaknesses.

AI prompt injection attack is one such vulnerability. It was first reported to OpenAI by Jon Cefalu in May 2022. Initially, it was not released to the public due to internal reasons but was brought forward among the public in September 2022 by Riley Goodside.

All thanks to Riley, the world came to know about the possibility of framing an input that can manipulate the language model into changing its expected behaviour aka the “AI prompt injection attack”.

This blog will teach you about AI prompt injection attacks and also introduce you to some safeguards to protect yourself against AI prompt injection attacks.

First, let us start with understanding What are AI prompt injection attacks.