Security Blog
The latest news and insights from Google on security and safety on the Internet
FuzzBench: Fuzzer Benchmarking as a Service
2. März 2020
Posted by Jonathan Metzman, Abhishek Arya, Google OSS-Fuzz Team and László Szekeres, Google Software Analysis Team
We are excited to launch
FuzzBench
, a fully automated, open source, free service for evaluating fuzzers. The goal of FuzzBench is to make it painless to rigorously evaluate fuzzing research and make fuzzing research easier for the community to adopt.
Fuzzing
is an important bug finding technique. At Google, we’ve found tens of thousands of bugs (
1
,
2
) with fuzzers like libFuzzer and AFL. There are numerous research papers that either improve upon these tools (e.g. MOpt-AFL, AFLFast, etc) or introduce new techniques (e.g. Driller, QSYM, etc) for bug finding. However, it is hard to know how well these new tools and techniques generalize on a large set of real world programs. Though research normally includes evaluations, these
often have shortcomings
—they don't use a large and diverse set of real world benchmarks, use few trials, use short trials, or lack statistical tests to illustrate if findings are significant. This is understandable since full scale experiments can be prohibitively expensive for researchers. For example, a 24-hour, 10-trial, 10 fuzzer, 20 benchmark experiment would require 2,000 CPUs to complete in a day.
To help solve these issues the OSS-Fuzz team is launching FuzzBench, a fully automated, open source, free service. FuzzBench provides a framework for painlessly evaluating fuzzers in a reproducible way. To use FuzzBench, researchers can simply integrate a fuzzer and FuzzBench will run an experiment for 24 hours with many trials and real world benchmarks. Based on data from this experiment, FuzzBench will produce a report comparing the performance of the fuzzer to others and give insights into the strengths and weaknesses of each fuzzer. This should allow researchers to focus more of their time on perfecting techniques and less time setting up evaluations and dealing with existing fuzzers.
Integrating a fuzzer with FuzzBench is simple as most integrations are less than 50 lines of code (
example
). Once a fuzzer is integrated, it can fuzz almost all 250+
OSS-Fuzz projects
out of the box. We have already integrated
ten fuzzers
, including AFL, LibFuzzer, Honggfuzz, and several academic projects such as QSYM and Eclipser.
Reports include statistical tests to give an idea how likely it is that performance differences between fuzzers are simply due to chance, as well as the raw data so researchers can do their own analysis. Performance is determined by the amount of covered program edges, though we plan on adding crashes as a performance metric. You can view a sample report
here
.
How to Participate
Our goal is to develop FuzzBench with community contributions and input so that it becomes the gold standard for fuzzer evaluation. We invite members of the fuzzing research community to contribute their fuzzers and techniques, even while they are in development. Better evaluations will lead to more adoption and greater impact for fuzzing research.
We also encourage contributions of better ideas and techniques for evaluating fuzzers. Though we have made some progress on this problem, we have not solved it and we need the community’s help in developing these best practices.
Please join us by contributing to the
FuzzBench repo
on GitHub.
Keine Kommentare :
Kommentar veröffentlichen
Labels
#sharethemicincyber
#supplychain #security #opensource
android
android security
android tr
app security
big data
biometrics
blackhat
C++
chrome
chrome enterprise
chrome security
connected devices
CTF
diversity
encryption
federated learning
fuzzing
Gboard
google play
google play protect
hacking
interoperability
iot security
kubernetes
linux kernel
memory safety
Open Source
pha family highlights
pixel
privacy
private compute core
Rowhammer
rust
Security
security rewards program
sigstore
spyware
supply chain
targeted spyware
tensor
Titan M2
VDP
vulnerabilities
workshop
Archive
2024
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2023
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2022
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2021
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2020
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2019
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2018
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2017
Dez.
Nov.
Okt.
Sept.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2016
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2015
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
Jan.
2014
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Apr.
März
Feb.
Jan.
2013
Dez.
Nov.
Okt.
Aug.
Juni
Mai
Apr.
März
Feb.
Jan.
2012
Dez.
Sept.
Aug.
Juni
Mai
Apr.
März
Feb.
Jan.
2011
Dez.
Nov.
Okt.
Sept.
Aug.
Juli
Juni
Mai
Apr.
März
Feb.
2010
Nov.
Okt.
Sept.
Aug.
Juli
Mai
Apr.
März
2009
Nov.
Okt.
Aug.
Juli
Juni
März
2008
Dez.
Nov.
Okt.
Aug.
Juli
Mai
Feb.
2007
Nov.
Okt.
Sept.
Juli
Juni
Mai
Feed
Follow @google
Follow
Give us feedback in our
Product Forums
.
Follow
Keine Kommentare :
Kommentar veröffentlichen