  This paper presents a novel fuzzing framework, called MicroFuzz, specifically
designed for Microservices. Mocking-Assisted Seed Execution, Distributed
Tracing, Seed Refresh and Pipeline Parallelism approaches are adopted to
address the environmental complexities and dynamics of Microservices and
improve the efficiency of fuzzing. MicroFuzz has been successfully implemented
and deployed in Ant Group, a prominent FinTech company. Its performance has
been evaluated in three distinct industrial scenarios: normalized fuzzing,
iteration testing, and taint verification.Throughout five months of operation,
MicroFuzz has diligently analyzed a substantial codebase, consisting of 261
Apps with over 74.6 million lines of code (LOC). The framework's effectiveness
is evident in its detection of 5,718 potential quality or security risks, with
1,764 of them confirmed and fixed as actual security threats by software
specialists. Moreover, MicroFuzz significantly increased program coverage by
12.24% and detected program behavior by 38.42% in the iteration testing.
