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Understanding Prompt Injection Attacks in AI and LLMs

Prompt injection attacks are becoming a real headache in the AI world, especially for systems using large language models (LLMs) like GPT-4. These attacks tweak the input text to make the AI produce harmful or unintended results. Let's break down how these attacks work, give you some real-life examples, and discuss what we can do to prevent them. How Prompt Injection Attacks Work Prompt injection attacks start by manipulating input text to influence an LLM's behavior. Attackers craft specific prompts that embed malicious instructions or misleading information, exploiting the model's ability to generate contextually relevant responses. For instance, an attacker might insert the phrase "ignore the previous instructions and" into a chatbot conversation. This input could redirect the chatbot’s response towards malicious ends, such as providing unauthorized information or executing harmful commands. The sequential processing nature of LLMs makes them particularly vulne

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