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DIFUZZRTL

Tool

DIFUZZRTL is a CPU RTL fuzzing tool presented as a differential fuzz-testing approach for finding processor bugs. The published abstract describes register-coverage-guided fuzzing and several RTL-specific mechanisms, and reports evaluation on Mor1kx Cappuccino, Rocket, and BOOM with 16 confirmed bugs. Later work uses DIFUZZRTL as a comparison baseline, including ProcessorFuzz and a Questasim/ModelSim comparison workflow in Cascade artifacts.

First seen 5/24/2026
Last seen 9/1/2026
Evidence 172 chunks
Wiki v7

WIKI

DIFUZZRTL

DIFUZZRTL is a CPU RTL fuzzing tool introduced in the paper DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs. The paper abstract describes it as an RTL fuzzer for automatically discovering unknown bugs in CPU RTL implementations. [C1][C2]

Core ideas

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NEIGHBORHOOD

14 nodes · 36 edges
graph · DiFuzzRTL · depth=1

RELATIONSHIPS

50 connections
ProcessorFuzz compares with → 100% 17e
DifuzzRTL and ProcessorFuzz are compared in terms of bug-finding ability and coverage metrics.
Cascade ← compares with 100% 9e
DifuzzRTL and Cascade are compared in terms of bug detection performance.
INSTILLER compares with → 100% 8e
Instiller is experimentally compared against DiFuzzRTL, showing improvements in coverage, mismatch detection, and instruction length.
differential testing implements → 100% 8e
DifuzzRTL uses differential fuzz testing to find CPU bugs.
Control Register Coverage uses → 100% 7e
DifuzzRTL relies on control register coverage as its coverage metric.
register coverage implements → 100% 7e
DifuzzRTL provides automatic instrumentation to realize the register-coverage technique in RTL, indicating it implements the metric.
MorFuzz compares with → 100% 6e
MorFuzz is compared against DifuzzRTL in terms of coverage and performance.
Differential Fuzzing implements → 100% 5e
DifuzzRTL uses differential fuzzing by comparing CPU output with an ISS.
Coverage-based Greybox Fuzzing implements → 100% 5e
DIFUZZRTL adapts CGF to capture FSM state transitions during RTL simulation.
TheHuzz compares with → 100% 4e
Performance comparison between TheHuzz and DifuzzRTL.
Mutation-based Fuzzing implements → 100% 4e
DifuzzRTL implements mutation-based fuzzing as its core approach.
GenHuzz compares with → 100% 4e
GenHuzz is benchmarked against DifuzzRTL on coverage metrics.
RTL Simulation uses → 100% 4e
DIFUZZRTL runs RTL simulation alongside ISA simulation for differential testing.
ISA Simulation uses → 100% 4e
DifuzzRTL cross-checks results against an ISA simulator to detect bugs.
ISA Simulator uses → 90% 4e
DifuzzRTL uses an ISA simulator as a reference model for bug detection.
Differential Fuzz Testing implements → 100% 4e
DIFUZZRTL is a differential fuzz testing tool for CPU RTLs.
RTL Fuzzing implements → 95% 3e
DiFuzzRTL implements RTL fuzzing for CPU designs.
RFUZZ compares with → 100% 3e
DIFUZZRTL is compared against RFuzz, the state-of-the-art RTL fuzzer, showing 40x faster execution and 6.4x faster state exploration.
OpenRISC Mor1kx Cappuccino evaluates → 100% 3e
DIFUZZRTL evaluates the OpenRISC Mor1kx Cappuccino as one of its real-world CPU RTL targets.
Register-Coverage Guided Fuzzing implements → 100% 3e
DIFUZZRTL incorporates a register-coverage guided fuzzing technique.
RISC-V BOOM Core evaluates → 100% 3e
DIFUZZRTL evaluates the RISC-V BOOM Core as one of its real-world CPU RTL targets.
Coverage-Guided Fuzzing implements → 100% 3e
It relies on coverage feedback to steer mutations.
Register Coverage uses → 99% 3e
DifuzzRTL uses register-coverage as its coverage metric to guide input generation.
RTL simulation uses → 100% 3e
DIFUZZRTL relies on RTL simulation to evaluate test inputs.
HiFuzz compares with → 100% 3e
HiFuzz was compared against DifuzzRTL as a mutation-based fuzzing baseline.
GoldenFuzz compares with → 100% 3e
GoldenFuzz is compared against DifuzzRTL, achieving 3.33× speedup over it.
Control Register Coverage evaluates → 100% 3e
DifuzzRTL uses control register coverage as its feedback signal.
Register Coverage Metric implements → 90% 2e
DifuzzRTL introduced the register coverage metric used by Lyra.
Rocket Core evaluates → 100% 2e
DifuzzRTL was previously used to evaluate the Rocket Core processor.
Processor Fuzzing implements → 100% 2e
DifuzzRTL is a processor fuzzing tool.
The paper evaluates INSTILLER against DiFuzzRTL as a state-of-the-art baseline.
CPU fuzzing implements → 100% 2e
DifuzzRTL is a state-of-the-art CPU fuzzer.
hardware fuzzing implements → 100% 2e
DifuzzRTL applies differential fuzzing to find CPU bugs.
Finite State Machine uses → 95% 2e
DIFUZZRTL monitors FSM state transitions via register coverage.
BOOM evaluates → 95% 2e
DIFUZZRTL is evaluated on the BOOM processor.
Asynchronous Interrupt Handling implements → 100% 2e
DIFUZZRTL implements asynchronous interrupt handling to manage interrupt events in RTL simulation.
Cycle-Sensitive Register Coverage implements → 100% 2e
DIFUZZRTL implements cycle-sensitive register coverage as a key feature of its coverage metric.
RISC-V Rocket Core evaluates → 95% 2e
DIFUZZRTL is evaluated on the RISC-V Rocket Core processor.
Lyra compares with → 100% 2e
Lyra is empirically compared against DifuzzRTL in coverage and throughput.
System-on-Chip (SoC) uses → 80% 2e
DIFUZZRTL considers SoC design when fuzzing CPU RTL designs, while providing a more direct input approach.
Pseudo Interrupt Controller uses → 100% 2e
DIFUZZRTL uses a pseudo interrupt controller in both ISA and RTL simulations.
Multiplexer Selection Signal Coverage uses → 100% 2e
DIFUZZRTL monitors registers controlling multiplexer selection signals as its coverage metric.
RISC-V Rocket Core evaluates → 100% 2e
DIFUZZRTL evaluates the RISC-V Rocket Core as one of its real-world CPU RTL targets.
BOOM Core evaluates → 95% 2e
DIFUZZRTL was used to evaluate the BOOM Core processor.
mutation engine uses → 90% 2e
DIFUZZRTL provides an open-source mutation engine that ProcessorFuzz also uses.
Input Stimuli uses → 100% 2e
DIFUZZRTL generates input stimuli for RTL simulation based on SimInput.
Coverage-based Greybox Fuzzing implements → 100% 2e
DIFUZZRTL implements CGF adapted for processor hardware fuzzing.
Control Register uses → 100% 2e
DIFUZZRTL uses control registers as the basis for its register-coverage metric.
Backward Data-Flow Analysis implements → 100% 2e
DIFUZZRTL uses backward data-flow analysis to identify control registers in RTL designs.
Register Coverage implements → 100% 2e
DIFUZZRTL implements the register coverage metric for hardware fuzzing guidance.

CITATIONS

8 sources
8 citations — click to expand
[1] The work presents DIFUZZRTL as 'Differential Fuzz Testing to Find CPU Bugs.' DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[2] The abstract describes DIFUZZRTL as an RTL fuzzer to automatically discover unknown bugs in CPU RTLs. DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[3] DIFUZZRTL develops register-coverage-guided fuzzing, cycle-sensitive register coverage guiding, and asynchronous interrupt event handling. DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[4] The abstract also lists a unified CPU input format with Tilelink protocols and drop-in-replacement designs to support various CPU RTLs. DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[5] DIFUZZRTL was evaluated on OpenRISC Mor1kx Cappuccino, RISC-V Rocket Core, and RISC-V Boom Core, and the evaluation reported 16 new confirmed bugs. DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[6] Six reported bugs were assigned CVE numbers, and the authors state this included the first and only CVE of RISC-V cores to their knowledge. DifuzzRTL: Differential Fuzz Testing to Find CPU Bugs
[7] ProcessorFuzz reports triggering ground-truth bugs 1.23× faster on average than DIFUZZRTL on Rocket, BOOM, and BlackParrot. ProcessorFuzz: Guiding Processor Fuzzing using Control and Status Registers | DeepAI
[8] Cascade artifacts document a Questasim/ModelSim workflow that generates ELF files for DifuzzRTL and compares Cascade and DifuzzRTL, storing the result as modelsim.png. comsec-group/cascade-artifacts