一句话：提出零配置模糊测试生成技术，通过变异请求与后端响应，最大化微服务内部状态覆盖并发现真实错误。
微服务架构虽带来可扩展性与灵活性，也引入新的安全挑战。本文提出一种零配置的微服务模糊测试生成技术，用于在无需人工配置的情况下自动构造测试。该方法同时变异进入微服务的请求以及其依赖服务返回的后端响应，以最大化对内部状态的覆盖。作者将技术部署到 Google 内部微服务平台中超过 95% 的 C++ 服务上，在真实微服务应用中报告并促成修复了数千个错误，表明该技术具有工业级可扩展性与有效性。
The microservice paradigm is a popular software development pattern that breaks down a large application into smaller, independent services. While this approach offers several advantages, such as scalability, agility, and flexibility, it also introduces new security challenges. This paper presents a novel approach to securing microservice architectures using fuzz testing. Fuzz testing is known to find programming errors in software by feeding it with unexpected or random inputs. In this paper, we propose a zero-config fuzz test generation technique for microservices that can maximize coverage of internal states by mutating both the incoming requests and the backend responses from dependent services. We successfully deployed our technique to over 95 % of C++ services built on Google's internal microservice platform. It reported and got fixed thousands of errors in real-world microservice applications.