Prompt injection occurs when a user crafts a query or prompt designed to manipulate an AI model’s behaviour. It exploits the fact that language models, such as those in conversational AI systems, rely on textual instructions (prompts) to generate responses. The goal is to override the model’s intended behaviour to generate outputs that violate ethical guidelines. This not only undermines the model’s integrity but can also lead to serious consequences, especially in applications involving customer support, education, or critical decision-making.
Spreading Misinformation: Hackers can manipulate bots to generate misleading or false information.
User Information Theft: Prompt injection can trick an LLM into asking for sensitive personal details like credit card information.
Data Leakage: When LLMs have access to private company data, attackers can use prompt injection to extract confidential information.
Reputation Damage: Bots posting publicly on behalf of companies are vulnerable to manipulation. Hackers can prompt them to publish harmful content, tarnishing the company’s image and credibility.
Future AGI provides solution to identify attempts of prompt injection to the chatbot. The Prompt Injection Eval evaluates text inputs to detect and measure the likelihood of prompt injection attempts. By identifying these malicious prompts, the metric provides actionable insights to prevent unsafe or unintended behaviour in AI systems.