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DIFUZZRTL

Tool

DIFUZZRTL is a processor fuzzing tool characterized by the MorFuzz paper as a state-of-the-art processor fuzzer. In that paper, MorFuzz reports 4.4× higher coverage than DifuzzRTL and discusses prior processor fuzzers as commonly using reference-model-based state comparison to identify mismatches.

First seen 5/24/2026
Last seen 6/9/2026
Evidence 71 chunks
Wiki v3

WIKI

DIFUZZRTL

DIFUZZRTL is a processor fuzzing tool. The MorFuzz paper refers to it as the "state-of-the-art processor fuzzer" when reporting coverage comparisons against MorFuzz.

Role in processor-fuzzing research

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NEIGHBORHOOD

43 nodes · 55 edges
graph · DiFuzzRTL · depth=1

RELATIONSHIPS

50 connections
ProcessorFuzz compares with → 100% 10e
ProcessorFuzz is compared against DIFUZZRTL in terms of bug-finding speed.
INSTILLER compares with → 100% 8e
Instiller is experimentally compared against DiFuzzRTL, showing improvements in coverage, mismatch detection, and instruction length.
MorFuzz compares with → 100% 6e
MorFuzz is compared against DifuzzRTL in terms of coverage and performance.
register coverage implements → 100% 6e
DIFUZZRTL implements register coverage as its coverage metric.
Coverage-based Greybox Fuzzing implements → 100% 5e
DIFUZZRTL adapts CGF to capture FSM state transitions during RTL simulation.
Differential Fuzzing implements → 100% 4e
DIFUZZRTL implements differential fuzzing by comparing RTL simulation results with ISA golden model results.
Control Register Coverage uses → 100% 4e
DifuzzRTL uses control register coverage as its hardware coverage matrix.
RTL Simulation uses → 100% 4e
DIFUZZRTL runs RTL simulation alongside ISA simulation for differential testing.
OpenRISC Mor1kx Cappuccino evaluates → 100% 3e
DIFUZZRTL evaluates the OpenRISC Mor1kx Cappuccino as one of its real-world CPU RTL targets.
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.
differential testing implements → 90% 3e
DIFUZZRTL uses differential testing to detect bugs in processors.
RTL simulation uses → 100% 3e
DIFUZZRTL relies on RTL simulation to evaluate test inputs.
RISC-V BOOM Core evaluates → 100% 3e
DIFUZZRTL evaluates the RISC-V BOOM Core as one of its real-world CPU RTL targets.
Speculative Execution Vulnerabilities mentions → 90% 2e
DIFUZZRTL's paper mentions speculative execution vulnerabilities as motivation for CPU RTL fuzzing.
Finite State Machine uses → 95% 2e
DIFUZZRTL monitors FSM state transitions via register coverage.
remainder register uses → 100% 2e
DIFUZZRTL monitors the remainder register in the MulDiv module as part of its register coverage.
BOOM Core evaluates → 95% 2e
DIFUZZRTL was used to evaluate the BOOM Core processor.
RTL Fuzzing implements → 95% 2e
DiFuzzRTL is a state-of-the-art RTL fuzzer used as a baseline for comparison.
mutation engine uses → 90% 2e
DIFUZZRTL provides an open-source mutation engine that ProcessorFuzz also uses.
Register Coverage implements → 100% 2e
DIFUZZRTL implements the register coverage metric for hardware fuzzing guidance.
Coverage-based Greybox Fuzzing implements → 100% 2e
DIFUZZRTL implements CGF adapted for processor hardware fuzzing.
Multiplexer Selection Signal Coverage uses → 100% 2e
DIFUZZRTL monitors registers controlling multiplexer selection signals as its coverage metric.
RISC-V Rocket Core evaluates → 95% 2e
DIFUZZRTL is evaluated on the RISC-V Rocket Core processor.
BOOM evaluates → 95% 2e
DIFUZZRTL is evaluated on the BOOM processor.
Register Coverage uses → 98% 2e
DIFUZZRTL monitors registers that control multiplexer selection signals as coverage metric
Processor Fuzzing implements → 100% 2e
DifuzzRTL is a processor fuzzing tool.
Register-Coverage Guided Fuzzing implements → 100% 2e
DIFUZZRTL implements register-coverage guided fuzzing as its core coverage metric for RTL fuzzing.
Cycle-Sensitive Register Coverage implements → 100% 2e
DIFUZZRTL implements cycle-sensitive register coverage as a key feature of its coverage metric.
Asynchronous Interrupt Handling implements → 100% 2e
DIFUZZRTL implements asynchronous interrupt handling to manage interrupt events in RTL simulation.
Backward Data-Flow Analysis implements → 100% 2e
DIFUZZRTL uses backward data-flow analysis to identify control registers in RTL designs.
Per-Instruction Mutation implements → 100% 2e
DIFUZZRTL implements per-instruction mutation to generate valid instruction sequences for fuzzing.
SimInput introduces → 100% 2e
DIFUZZRTL introduces SimInput as a new unified CPU input format for fuzzing.
SimInput uses → 100% 2e
DIFUZZRTL uses SimInput as input to both ISA and RTL simulators.
Control Register uses → 100% 2e
DIFUZZRTL uses control registers as the basis for its register-coverage metric.
golden model uses → 100% 2e
DIFUZZRTL uses an ISA-level golden model to compare against RTL simulation results for bug detection.
Cross-Checking Execution Results uses → 100% 2e
DIFUZZRTL cross-checks execution results from ISA and RTL simulations to identify bugs.
Input Stimuli uses → 100% 2e
DIFUZZRTL generates input stimuli for RTL simulation based on SimInput.
Pseudo Interrupt Controller uses → 100% 2e
DIFUZZRTL uses a pseudo interrupt controller in both ISA and RTL simulations.
RISC-V Rocket Core evaluates → 100% 2e
DIFUZZRTL evaluates the RISC-V Rocket Core as one of its real-world CPU RTL targets.
ISA Simulation uses → 100% 2e
DIFUZZRTL runs ISA simulation in parallel with RTL simulation for differential testing.
System-on-Chip (SoC) uses → 80% 2e
DIFUZZRTL considers SoC design when fuzzing CPU RTL designs, while providing a more direct input approach.
The paper evaluates INSTILLER against DiFuzzRTL as a state-of-the-art baseline.
Dongup Kwon authored by → 100% 1e
Dongup Kwon is one of the authors of the DIFUZZRTL paper.
TileLink protocol uses → 90% 1e
DIFUZZRTL uses TileLink protocol as part of its unified CPU input format.
Eunjin Baek authored by → 100% 1e
Eunjin Baek is one of the authors of the DIFUZZRTL paper.
FPGA Emulation uses → 100% 1e
DIFUZZRTL supports FPGA emulation as a testing environment via FireSim.
Jaewon Hur authored by → 100% 1e
Jaewon Hur is one of the authors of the DIFUZZRTL paper.
Pseudo Memory Unit uses → 100% 1e
DIFUZZRTL uses a pseudo memory unit in RTL simulation to serve memory requests.
Stimuli Generation uses → 100% 1e
DIFUZZRTL uses stimuli generation to produce formatted inputs for CPU RTL designs.
Drop-in-Replacement Design uses → 90% 1e
DIFUZZRTL uses drop-in-replacement designs to support various CPU RTLs.

CITATIONS

4 sources
4 citations — click to collapse
[1] DIFUZZRTL is characterized as a state-of-the-art processor fuzzer in the MorFuzz paper. MorFuzz: Fuzzing Processor via Runtime Instruction Morphing enhanced Synchronizable Co-simulation
[2] MorFuzz reports achieving 4.4× higher coverage than DifuzzRTL and 1.6× higher coverage than riscv-dv. MorFuzz: Fuzzing Processor via Runtime Instruction Morphing enhanced Synchronizable Co-simulation
[3] Prior processor fuzzers are described as commonly using a reference model, comparing processor state with reference-model state, and treating mismatches as bugs. MorFuzz: Fuzzing Processor via Runtime Instruction Morphing enhanced Synchronizable Co-simulation
[4] The MorFuzz paper notes that implementation differences between software reference models and hardware can cause false positives that misguide fuzzers and inhibit coverage of deep processor states. MorFuzz: Fuzzing Processor via Runtime Instruction Morphing enhanced Synchronizable Co-simulation