Google unveiled a new framework known as Project Naptime designed to enhance vulnerability research using large language models (LLM) and automated discovery techniques.
According to Google Project Zero researchers Sergei Glazunov and Mark Brand who stated that the Naptime architecture involves an AI agent interacting with a target codebase, equipped with specialized tools to mimic human security researchers’ workflow.
Named for its ability to assist with vulnerability research and automate variant analysis while humans “take regular naps,” the approach leverages LLMs’ code comprehension and reasoning to identify security vulnerabilities.
Key components include a Code Browser tool for navigating the codebase, a Python tool for running scripts in a sandbox for fuzzing, a Debugger tool to observe program behavior, and a Reporter tool to track task progress.
Google noted that Naptime is model-agnostic and backend-agnostic, offering improved detection of buffer overflow and memory corruption issues compared to OpenAI GPT-4 Turbo based on CYBERSECEVAL 2 benchmarks.
Testing by Google showed higher scores for vulnerability categories using Naptime, indicating the AI’s ability to mimic human security experts’ iterative approach accurately and produce reproducible results.
