ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers

Paper WIKI v1 · 6/29/2026

A 2022 paper that introduces ProcessorFuzz, a processor fuzzing approach guided by a CSR-transition coverage metric. The paper presents an HDL-agnostic workflow that uses CSR transitions observed in ISA traces to identify interesting inputs for RTL checking, and reports faster triggering of ground-truth bugs than DIFUZZRTL as well as nine confirmed bugs.

Overview

ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers presents ProcessorFuzz, a processor fuzzer that uses a CSR-transition coverage metric to guide exploration of processor states. The paper is motivated by limitations in prior RTL hardware fuzzing, including lack of support for widely used HDLs and misleading coverage signals that can misidentify interesting inputs. [1]

Core idea

The main idea is to monitor transitions in control and status registers (CSRs). The paper argues that CSRs control and hold processor state, so a transition in CSR values indicates a new processor state. ProcessorFuzz therefore uses newly observed CSR transitions as feedback to guide fuzzing toward previously unexplored states. [2]

Design

ProcessorFuzz is described as HDL-agnostic and as requiring no instrumentation in the processor design itself. In the design flow described in the paper, ProcessorFuzz first runs an ISA simulator on inputs generated by its mutation engine and produces an extended ISA trace log containing CSR values. A transition unit extracts CSR transitions, checks whether each transition is new using a transition map, and records newly seen transitions. Only inputs deemed interesting are then executed in RTL simulation; the resulting RTL trace is compared against the ISA trace, and any mismatch is treated as a potential bug that typically requires manual confirmation. [2][3]

Evaluation

The paper evaluates ProcessorFuzz on three real-world open-source processors: Rocket, BOOM, and BlackParrot. Compared with DIFUZZRTL, ProcessorFuzz triggered a set of ground-truth bugs 1.23× faster on average. The reported experiments also exposed 8 new bugs across the three RISC-V cores and 1 new bug in a reference model, with all nine bugs confirmed by the corresponding developers. [4]

Publication details

The paper was published on arXiv in September 2022. The authors listed in the provided evidence are Sadullah Canakci, Chathura Rajapaksha, Anoop Mysore Nataraja, Leila Delshadtehrani, Michael Taylor, Manuel Egele, and Ajay Joshi. [5]

LINKED ENTITIES

7 links

ProcessorFuzz INTRODUCES

CSR-transition coverage metric INTRODUCES

DiFuzzRTL EVALUATES

hardware fuzzing MENTIONS

Processor Fuzzing MENTIONS

CSRs MENTIONS

Coverage signals MENTIONS

CITATIONS

5 sources

5 citations

[1] [1] Prior RTL hardware fuzzing has limitations including lack of support for widely used HDLs and misleading coverage signals. ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers | DeepAI

[2] [2] ProcessorFuzz introduces a CSR-transition coverage metric; CSR transitions are used as indicators of new processor states; the approach is HDL-agnostic and does not require instrumentation in the processor design. ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers | DeepAI

[3] [3] Design flow: ISA simulation produces an extended ISA trace log with CSR values, a transition unit extracts and records new CSR transitions via a transition map, only interesting inputs proceed to RTL simulation, and ISA/RTL mismatches indicate potential bugs. [PDF] Guiding Processor Fuzzing using Control and Status Registers - arXiv

[4] [4] Evaluation uses Rocket, BOOM, and BlackParrot; ProcessorFuzz triggers ground-truth bugs 1.23× faster on average than DIFUZZRTL; experiments found 8 new bugs in the three RISC-V cores and 1 in a reference model, all confirmed by developers. ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers | DeepAI

[5] [5] The paper was published in September 2022 on arXiv, and the listed authors are Sadullah Canakci, Chathura Rajapaksha, Anoop Mysore Nataraja, Leila Delshadtehrani, Michael Taylor, Manuel Egele, and Ajay Joshi. New Processor Fuzzing Mechanism