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CITATION.cff
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cff-version: 1.2.0
title: 'OSS-Fuzz-Gen: Automated Fuzz Target Generation'
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Dongge
family-names: Liu
email: [email protected]
affiliation: Google LLC
orcid: 'https://orcid.org/0000-0003-4821-7033'
- given-names: Oliver
family-names: Chang
email: [email protected]
affiliation: Google LLC
orcid: 'https://orcid.org/0009-0006-3181-4551'
- given-names: Jonathan
family-names: metzman
email: [email protected]
affiliation: Google LLC
orcid: 'https://orcid.org/0000-0002-7042-0444'
- given-names: Martin
family-names: Sablotny
email: [email protected]
affiliation: NVIDIA
orcid: 'https://orcid.org/0000-0002-9836-8254'
- given-names: Mihai
family-names: Maruseac
email: [email protected]
affiliation: Google LLC
orcid: 'https://orcid.org/0000-0002-6225-1206'
repository-code: 'https://github.com/google/oss-fuzz-gen'
url: >-
https://security.googleblog.com/2023/08/ai-powered-fuzzing-breaking-bug-hunting.html
abstract: >-
OSS-Fuzz-Gen, an innovative open-source project developed
by Google, automates fuzz target generation to enhance
software security and reliability. Utilizing advanced
techniques, including large language models (LLM), static
code analysis, and runtime crash diagnosis, this project
efficiently creates and optimizes fuzz targets. These
efforts increase code coverage and identify
vulnerabilities within open-source projects. We actively
encourage and support collaborations with the research and
open-source communities, offering our services at no cost.
keywords:
- Fuzzing
- Fuzz target generation
- Large Language Models
- Open-source
- Code analysis
- Software security
license: Apache-2.0
version: 'https://github.com/google/oss-fuzz-gen/tree/v1.0'
date-released: '2024-05-02'