spatwei writes: Google has used a large language model (LLM) agent called “Big Sleep” to discover a previously unknown, exploitable memory flaw in a widely used software for the first time, the company announced Friday.
The stack buffer underflow vulnerability in a development version of the popular open-source database engine SQLite was found through variant analysis by Big Sleep, which is a collaboration between Google Project Zero and Google DeepMind.
Big Sleep is an evolution of Project Zero’s Naptime project, which is a framework announced in June that enables LLMs to autonomously perform basic vulnerability research. The framework provides LLMs with tools to test software for potential flaws in a human-like workflow, including a code browser, debugger, reporter tool and sandbox environment for running Python scripts and recording outputs.
The researchers provided the Gemini 1.5 Pro-driven AI agent with the starting point of a previous SQLIte vulnerability, providing context for Big Sleep to search for potential similar vulnerabilities in newer versions of the software. The agent was presented with recent commit messages and diff changes and asked to review the SQLite repository for unresolved issues.
Google’s Big Sleep ultimately identified a flaw involving the function “seriesBestIndex” mishandling the use of the special sentinel value -1 in the iColumn field. Since this field would typically be non-negative, all code that interacts with this field must be designed to handle this unique case properly, which seriesBestIndex fails to do, leading to a stack buffer underflow.
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