Hardware fuzzing has become a compelling automated verification method for efficiently identifying hardware bugs. However, current fuzzers predominantly focus on maximizing overall coverage, often overlooking the coverage of individual modules. This oversight leads to insufficient testing of low-coverage yet functionally critical modules and leaves essential inter-module dependencies unexplored. Consequently, effectively and efficiently verifying processor modules remains an unresolved challenge. In order to achieve focused exploration of low-coverage modules and effectively capture inter-module dependencies, we propose ModFuzz, a novel adaptive module-level processor fuzzer. We divide the processor into modules and dynamically adjust their priorities based on the Nondominated Sorting Genetic Algorithm II (NSGA-II). By selecting the highest-priority module and applying Inter-Module Dependency Matrix (IMDM)-driven seed selection, ModFuzz concentrates fuzz testing on low-coverage modules and high-dependency seeds. We evaluated ModFuzz on five popular open source RISC-V processors and discovered 16 new bugs with varying degrees of complexity, each of which received a CVE assignment. Compared to the representative CPU fuzzers DifuzzRTL and ProcessorFuzz, ModFuzz improves module coverage by an average of 4.35× and 4.44×, respectively, and increases overall coverage by an average of 4.16× and 3.97×. Our experimental results demonstrate that ModFuzz effectively detects processor bugs while significantly enhancing both the module and the overall coverage.