Imagine trying to understand a complex conversation by only hearing snippets. That's the challenge of traditional methods for analyzing network protocols. They often miss crucial interactions, leaving vulnerabilities hidden. Researchers are now turning to Large Language Models (LLMs), the brains behind AI chatbots, to crack the code. These LLMs can analyze the actual implementation of a protocol, going beyond the official documentation (RFCs) to understand how it truly works. By carefully "prompting" the LLM, researchers can extract the protocol's "state machine," a blueprint of its behavior. This blueprint reveals the different states of a protocol (like "connected" or "waiting") and how it transitions between them. This approach, called ProtocolGPT, achieves over 90% accuracy in extracting state machines from complex protocols like TLS and BGP. Why does this matter? Knowing a protocol's true state machine helps security researchers find vulnerabilities more effectively. It's like having a map of all the possible paths a conversation can take, making it easier to spot the dangerous ones. This research opens exciting possibilities for improving protocol security and building more robust network systems. However, challenges remain. LLMs have limitations in handling massive codebases, requiring researchers to break down the code into smaller chunks. The future of protocol analysis likely lies in combining the power of LLMs with other techniques to overcome these limitations and unlock even deeper insights into the complex world of network communication.