CPU fuzzing

Technique

In the provided evidence, CPU fuzzing is represented primarily by Cascade, a USENIX Security 2024 system for CPU fuzzing via intricate program generation. The evidence emphasizes generated program inputs, reuse of inputs across compatible ISA-related designs, throughput tradeoffs between program length and generation cost, and Cascade's no-runtime-overhead design. Separate public context on CuFuzz also treats established CPU fuzzing tools as the baseline being extended to GPU code.

First seen 6/10/2026

Last seen 8/5/2026

Evidence 13 chunks

Wiki v2

WIKI

Overview

In the supplied evidence, CPU fuzzing is characterized mainly through Cascade, a 2024 USENIX Security work titled Cascade: CPU Fuzzing via Intricate Program Generation. The strongest technical emphasis is on generating programs for CPUs under test and evaluating how generation cost interacts with fuzzing throughput.

Evidence-backed characteristics

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NEIGHBORHOOD

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RELATIONSHIPS

5 connections

Cascade ← implements 100% 3e

The title ties Cascade directly to CPU fuzzing, implying the tool embodies that technique.

DiFuzzRTL ← implements 100% 2e

DifuzzRTL is a state-of-the-art CPU fuzzer.

Cascade: CPU fuzzing via intricate program generation ← mentions 95% 1e

CPU fuzzing appears in the paper's title, indicating it is a central topic.

RFUZZ ← implements 100% 1e

RFUZZ is a state-of-the-art CPU fuzzer.

LiFU ← implements 100% 1e

LiFU is a CPU fuzzing framework.

LINKED ENTITIES

1 links

Cascade IMPLEMENTS Extracted graph relationship

CITATIONS

7 sources

7 citations — click to expand

[1] Cascade is a paper titled 'Cascade: CPU Fuzzing via Intricate Program Generation' by Flavien Solt, Katharina Ceesay-Seitz, and Kaveh Razavi, published at USENIX Security 2024. Cascade: CPU Fuzzing via Intricate Program Generation - USENIX

[2] Cascade's evaluation measures time spent in intermediate program construction, asymmetric ISA pre-simulation, and RTL simulation over 24 hours of fuzzing. Cascade: CPU Fuzzing via Intricate Program Generation

[3] Cascade's inputs are reusable across designs that share compatible ISA extensions and across CPU generations, so input generation can be amortized. Cascade: CPU Fuzzing via Intricate Program Generation

[4] Cascade compares against RFUZZ and DifuzzRTL, relies on paper-reported TheHuzz results, and reports no runtime overhead by design; the excerpt cites 6.1%-6.9% and 97% overheads for DifuzzRTL modes and 71% for TheHuzz. Cascade: CPU Fuzzing via Intricate Program Generation

[5] When including generation time, programs of about 10k instructions generally provide the best effective fuzzing throughput in Cascade. Cascade: CPU Fuzzing via Intricate Program Generation

[6] The provided Cascade excerpt says the system was tested on CPUs ranging from PicoRV32 to BOOM and that Cascade was implemented as 6k lines of Python code. Cascade: CPU Fuzzing via Intricate Program Generation

[7] The public-context paper CuFuzz describes fuzzing as effective for finding such bugs on CPUs and presents a way to extend state-of-the-art CPU fuzzing tools to GPU programs because equivalent GPU tools are lacking. CuFuzz: Hardening CUDA Programs through Transformation and Fuzzing