This paper reports an attempt to solve the fill in the missing letters type CAPTCHA using generative AI. Many websites have adopted CAPTCHA to prevent bots and other automated programs from engaging in malicious activities such as posting comment spam. Text-based CAPTCHA is the most common and earliest form of CAPTCHA. However, as optical character recognition (OCR) technology has improved, the intensity of distortions applied to a CAPTCHA to keep it unrecognizable by OCR has also increased. This has reached a point where humans are having difficulty recognizing CAPTCHA text. The CAPTCHA proposed in the previous study asks users to spell a word by filling in some blanks. Since the number of letters displayed is minimal, it is challenging to identify the correct word. However, one or more images that can serve as hints to help users guess the answer word are also provided. It is expected that the ability to guess can distinguish between humans and computers. However, it is conceivable that generative AI, which has been advancing in recent years, can substitute for this ability. A series of experiments was carried out to evaluated the performance of the generative AI’s ability to solve the proposed CAPTCHA. First, we examined whether a well-known image recognition system could accurately identify the images used in the CAPTCHA problems. Next, we used the recognition results to have the generative AI solve the CAPTCHA problems and determined the accuracy rate. Additionally, we evaluated the performance of the generative AI itself by solving the problems using the correct identification of each image. From the experimental results, it was found that the CAPTCHA is relatively robust against attack techniques using generative AI.