Reference Library
Inside the Machine: A Deep Dive into LLM Security

Large language models inherit their deepest vulnerabilities not from sloppy engineering but from the mathematical architecture that makes them powerful. This deep-dive dissects the threat landscape from the transformer's attention mechanism up through infrastructure-level defenses, examining prompt injection, context window attacks, laundering, RAG poisoning, multimodal cross-modal injection, and the emerging challenge of agentic AI security.



