GoldenFuzz: Generative Golden Reference Hardware Fuzzing
Published:Dec 25, 2025 06:16
•1 min read
•ArXiv
Analysis
This article introduces GoldenFuzz, a new approach to hardware fuzzing using generative models. The core idea is to create a 'golden reference' and then use generative models to explore the input space, aiming to find discrepancies between the generated outputs and the golden reference. The use of generative models is a novel aspect, potentially allowing for more efficient and targeted fuzzing compared to traditional methods. The paper likely discusses the architecture, training, and evaluation of the generative model, as well as the effectiveness of GoldenFuzz in identifying hardware vulnerabilities. The source being ArXiv suggests a peer-review process is pending or has not yet occurred, so the claims should be viewed with some caution until validated.
Key Takeaways
- •GoldenFuzz is a new hardware fuzzing technique.
- •It uses generative models to create and compare against a 'golden reference'.
- •The approach aims to find hardware vulnerabilities.
- •The paper is likely available on ArXiv.
Reference
“The article likely details the architecture, training, and evaluation of the generative model used for fuzzing.”