LLMSGen: Generating Diverse Seeds for Multimedia Protocol Fuzzing Leveraging Large Language Models

Multimedia protocol implementations are susceptible to security vulnerabilities, yet the existing fuzzing methods fail to generate seed corpora covering all supported resource types due to the resource type sensitivity characteristic, resulting in limited code coverage. We propose LLMSGen, a method leveraging Large Language Models (LLMs) to generate diverse seeds for multimedia protocol fuzzing. Through prompt chaining, LLMs analyze the source code of the target program to identify supported resource types and extract URI construction rules. Diverse request seeds are then generated by replacing URI fields in captured traffic, and the corresponding resource files are placed in the server’s working directory to ensure valid responses during fuzzing. Evaluated on three RTSP-based open-source programs (Live555, RTSPServer, Gstreamer), LLMSGen increased resource type coverage by an average of approximately 98.4% and improved code line coverage by approximately 36.8% compared to AFLNet’s original seed corpus.