Every serious security topic in 2026 eventually requires understanding what a large language model actually is. Prompt injection, jailbreaking, model theft, adversarial inputs, hallucination exploitation — all of these attack categories only make sense once you understand the underlying architecture. My goal in this guide is to explain LLMs the way I explain them in security briefings: technically accurate, practically focused, and without the machine learning PhD prerequisites. If you understand how LLMs work, you understand why they're vulnerable in…
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