Practicalities of LLM guardrails — a demo by ML6

Practicalities of LLM guardrails — a demo by ML6

We have seen rapid integration of Large Language Model’s (LLM), like Chat-GPT, into applications and services. These powerful tools provide huge opportunities, but also face unique risks like prompt injections. This is because LLM’s are by default influenced by context and language and therefore can be persuaded to act differently than intended. In this post, we’ll look at essential guardrails to protect these applications from such attacks, ensuring they remain secure and reliable.

In the previous , where you can experiment with breaking different types of guardrails to gain a deeper understanding of their effectiveness and limitations. Checkout the demo here:

Secret Agent Guardrail Challenge – a Hugging Face Space by ml6team

By understanding common hacking techniques and the various guardrail strategies, you can now make informed decisions about how to best protect your LLM applications.

It is important to note that the field of LLM security is constantly evolving. New techniques and attacks may emerge, making it challenging to develop guardrails that are 100% foolproof. Therefore, we encourage ongoing research, development, and collaboration to ensure the continued security and reliability of LLMs. By staying informed and proactive, you can mitigate the risks associated with these powerful technologies and harness their full potential.

Additionally this vulnerability of LLM’s shows that we have to be careful what information and data is supplied in the prompt templates in the first place. Sensitive or confidential information should be handled with caution to prevent unauthorised access or disclosure.

Final remark: In the demo, we only have a single input interaction with the LLM to demonstrate the guardrailing techniques. However in reality a lot of LLM applications are chat-based and therefore give the user the opportunity to break the application by guiding the LLM step-by-step to a desired outcome, instead of having to use a single prompt. This makes protecting against attacks even more difficult and needs to be kept in mind when building a chat application.

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