Large language models tap into natural language in an associative and statistical way, thereby acquiring capabilities that were previously reserved for human intelligence. However, this also makes them unreliable and vulnerable to attacks in natural language, e.g. prompt injections. It is particularly critical when LLM-based applications, such as chatbots, interact directly with users or make decisions. Language models can also exhibit unpredictable misbehaviour regardless of attacks and manipulation.

Depending on the application, they can cause serious damage. This cannot be prevented by explicit system instructions, access rights or by restricting the knowledge space using RAGs. The core problem: language models do not follow their instructions reliably.

It is therefore essential for the productive use of LLM applications to protect them against cyber attacks and manipulation and to monitor whether the language model used is following its instructions.

With LINK2AI.Monitor, we support companies in fully exploiting the enormous potential of generative AI without compromising on security and cost-effectiveness.