<ul data-eligibleForWebStory="false"><li>Large Language Models (LLMs) and Generative AI (GenAI) like OpenAI’s ChatGPT, Google’s Bard, and Anthropic’s Claude are revolutionizing industries with their seamless conversations but are facing emerging cybersecurity threats.</li><li>The article delves into the advanced cybersecurity risks in the LLM ecosystem: Prompt Injection, Data Poisoning, and Model Hijacking, highlighting the challenges to data integrity, model reliability, and user trust.</li><li>Prompt Injection involves attacking LLMs with clever inputs to cause unexpected or malicious behavior, emphasizing the importance of treating LLM prompts as code to mitigate risks.</li><li>Data Poisoning can subtly manipulate LLM behavior by injecting malicious data into training datasets, posing a significant risk to corporations relying on AI models, requiring enterprises to enhance data validation and security measures.</li></ul>

Cybersecurity in LLMs and GenAI Models: Prompt Injection, Data Poisoning, and Model Hijacking

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