One of Google's "big AI" projects uncovered some serious security threats seemingly all on its own
Big Sleep discovers memory safety on its own
- Project Zero and DeepMind "big AI" uncovers security vulnerabilities
- Big Sleep finds a SQLite stack buffer underflow flaw before official release
- AI could revolutionize software development by discovering critical flaws
A collaborative “big AI” project between Google Project Zero and Google DeepMind has discovered a critical vulnerability in a piece of software before public release.
The Big Sleep AI agent was set to work analyzing the SQLite open source database engine, where it discovered a stack buffer underflow flaw which was subsequently patched the same day.
This discovery potentially marks the first ever time an AI has uncovered a memory-safety flaw in a widely used application.
Fuzzed software out-fuzzed by AI
Big Sleep found the stack buffer underflow vulnerability in SQLite which had been ‘fuzzed’ multiple times.
Fuzzing is an automated software testing method that can discover potential flaws or vulnerabilities such as memory safety issues that are typically exploited by attackers. However, it is not a foolproof method of vulnerability hunting, and a fuzzed vulnerability that is found and patched could also exist as a variant elsewhere in the software and go undiscovered.
The methodology used by Google in this instance was to provide a previously patched vulnerability as a starting point for the Big Sleep agent, and then set it loose hunting for similar vulnerabilities elsewhere in the software.
While hunting for a similar vulnerability, Big Sleep encountered a vulnerability and traced the steps it took to recreate the vulnerability in a test case, gradually narrowing down the potential causes to a single issue and generating an accurate summary of the vulnerability.
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Google Project Zero points out that the bug wasn’t previously spotted using traditional fuzzing techniques as the fuzzing harness was not configured to access the same extensions. However, when fuzzing was re-run with the same configurations, the vulnerability remained undiscovered despite 150 CPU-hours of fuzzing.
“We hope that in the future this effort will lead to a significant advantage to defenders - with the potential not only to find crashing testcases, but also to provide high-quality root-cause analysis, triaging and fixing issues could be much cheaper and more effective in the future,” the Big Sleep team said. “We aim to continue sharing our research in this space, keeping the gap between the public state-of-the-art and private state-of-the-art as small as possible.”
The full testing methodology and vulnerability discovery details can be found here.
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Benedict is a Senior Security Writer at TechRadar Pro, where he has specialized in covering the intersection of geopolitics, cyber-warfare, and business security.
Benedict provides detailed analysis on state-sponsored threat actors, APT groups, and the protection of critical national infrastructure, with his reporting bridging the gap between technical threat intelligence and B2B security strategy.
Benedict holds an MA (Distinction) in Security, Intelligence, and Diplomacy from the University of Buckingham Centre for Security and Intelligence Studies (BUCSIS), with his specialization providing him with a robust academic framework for deconstructing complex international conflicts and intelligence operations, and the ability to translate intricate security data into actionable insights.