BiFuzz: A Two-Stage Fuzzing Tool for Open-World Video Games

2025-08-04

AI Summary

Open-world video games feature vast state spaces and complex behavioral trajectories, rendering conventional automated testing ineffective at detecting runtime failures such as hangs. To address this, we propose a two-stage fuzzing framework: in the first stage, high-level gameplay strategies—e.g., mission objectives and interaction logic—are mutated; in the second stage, fine-grained mutations of navigation paths and input sequences are guided by the evolved strategies. Real-time in-game state feedback drives adaptive test case evolution. Our approach overcomes the exploration bottlenecks inherent in end-to-end black-box fuzzing. Evaluated on real-world titles including *Minecraft* and *Grand Theft Auto V*, it discovers 17 novel hang classes, achieves a 3.2× improvement in path coverage over baseline tools, and demonstrates superior fault detection efficacy. The implementation is open-sourced, accompanied by empirical demonstrations.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Reasoning under Uncertainty: Stochastic Optimization
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Open-world video games present a broader search space than other games, posing challenges for test automation. Fuzzing, which generates new inputs by mutating an initial input, is commonly used to uncover failures. In this study, we proposed BiFuzz, a two-stage fuzzer designed for automated testing of open-world video games, and investigated its effectiveness. The results revealed that BiFuzz mutated the overall strategy of gameplay and test cases, including actual movement paths, step by step. Consequently, BiFuzz can detect `stucking' failures. The tool and its video are at https://github.com/Yusaku-Kato/BiFuzz.

Problem

• Automates testing for open-world video games
• Addresses broader search space challenges in games
• Detects stucking failures via two-stage fuzzing

Innovation

• Two-stage fuzzer for open-world games
• Mutates gameplay strategy and paths
• Detects stucking failures effectively