you are right that a traditional fuzzer (especially a grey-box one like AFL or a white-box one) is superior in speed, cost per execution, and comprehensiveness.
The argument for using an LLM to generate a curated set of fuzz inputs isn't to replace traditional fuzzers, but to complement them by targeting a different class of bugs that traditional fuzzers are often poor at finding.
The goal of this tool is two fold.
1. give LLMs the ability to make use of traditional software testing tools
2. enhance some of the shortcomings in traditional software testing tools by selectively using LLMs (specifically their ability to understand the larger context the code is written in)
