Web security is a constant arms race. Penetration testing, where ethical hackers probe for vulnerabilities, is crucial for protecting sensitive data. But what if AI could automate this process? New research explores the potential of Large Language Models (LLMs), the brains behind tools like ChatGPT, to automate penetration testing from start to finish. Researchers built a benchmark of common web vulnerabilities and tested various LLM-powered agents. The results are intriguing. While these AI agents understand the basics of penetration testing and can even use hacking tools, they struggle with complex scenarios. They get bogged down in details, misinterpret results, and sometimes even “hallucinate” incorrect commands. To overcome these limitations, the researchers developed AutoPT, a new system that guides the LLM using a state machine. Think of it like a roadmap that keeps the AI focused and efficient. AutoPT dramatically improved the success rate, especially for complex vulnerabilities. It even cut the time and cost compared to other LLM-based methods. While fully automated penetration testing isn’t here yet, this research suggests it's on the horizon. AutoPT’s performance raises important questions about the future of cybersecurity. As AI hacking tools become more sophisticated, we’ll need equally advanced defenses. The next phase of this research will likely focus on mitigating these potential threats and ensuring AI is used responsibly in the ongoing battle for web security.