Snappy: Efficient Fuzzing with Adaptive and Mutable Snapshots-Reference-Cited by-同舟云学术

Snappy: Efficient Fuzzing with Adaptive and Mutable Snapshots

Published:2022-12-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 38th Annual Computer Security Applications Conference
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Author:

Geretto Elia¹^ORCID,Giuffrida Cristiano¹^ORCID,Bos Herbert¹^ORCID,Van Der Kouwe Erik¹^ORCID

Affiliation:

1. Vrije Universiteit Amsterdam, Netherlands

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3564625.3564639

Reference37 articles.

1. [n.d.]. DataFlowSanitizer. https://clang.llvm.org/docs/DataFlowSanitizer.html. [n.d.]. DataFlowSanitizer. https://clang.llvm.org/docs/DataFlowSanitizer.html.

2. [n.d.]. libFuzzer. https://llvm.org/docs/LibFuzzer.html. [n.d.]. libFuzzer. https://llvm.org/docs/LibFuzzer.html.

3. Anastasios Andronidis and Cristian Cadar . 2022 . SnapFuzz: High-Throughput Fuzzing of Network Applications. In ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022) (Virtual Event). Anastasios Andronidis and Cristian Cadar. 2022. SnapFuzz: High-Throughput Fuzzing of Network Applications. In ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022) (Virtual Event).

4. NAUTILUS: Fishing for Deep Bugs with Grammars

5. REDQUEEN: Fuzzing with Input-to-State Correspondence

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