Prompt Injection: Large Language Model Security Risk

Organisations need to identify strategies to counteract this harmful cyberattack as generative AI applications grow more and more integrated into enterprise IT platforms

Hackers can use a technique known as “prompt injections” to trick an LLM application into accepting harmful text that is actually legitimate user input

The prompt’s wording, “when it comes to remote work and remote jobs,” drew the bot’s attention because it was designed to react to tweets regarding remote labour

LLM apps can stay ahead of hackers with regular updates and patching, just like traditional software. In contrast to GPT-3.5, GPT-4 is less sensitive to quick injections

Although it is challenging to parameterize inputs into an LLM, developers can at least do so for any data the LLM sends to plugins or APIs

Comparing the system prompt with human input Prompt injections can fool LLMs by imitating the syntax or language of system prompts

Hackers most frequently breach company networks by misusing legitimate user identities, according to the IBM X-Force Threat Intelligence Index