Finding instrumentable locations for fuzzing via static binary analysis

Today, the exploitation of vulnerabilities which exists in every software program is still prevalent, leading to unintended repercussions. This highlights the importance of eradicating the pre-existing vulnerabilities before they can be exploited by hackers. In this study, American Fuzzy Lop Plus Pl...

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Main Author: Ng, Lyon Hong Kai
Other Authors: Liu Yang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/156539
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1565392022-04-19T08:26:30Z Finding instrumentable locations for fuzzing via static binary analysis Ng, Lyon Hong Kai Liu Yang School of Computer Science and Engineering yangliu@ntu.edu.sg Engineering::Computer science and engineering Today, the exploitation of vulnerabilities which exists in every software program is still prevalent, leading to unintended repercussions. This highlights the importance of eradicating the pre-existing vulnerabilities before they can be exploited by hackers. In this study, American Fuzzy Lop Plus Plus (AFL++) was the fuzzer used to fuzz programs on the ubuntu system. The objective of this project is to find crashes that might lead to the discovery of vulnerabilities which were not documented before. The input files (seeds) consisted of mp4 files and binary files which were obtained from go-fuzz-corpus seed bank, as well as from submitted Proof-of-Concept (POC) files by other users. This paper provides a detailed explanation and highlights the steps for the fuzzing campaign done through a period of 10-12 months on the Program Under Test (PUT) with the seeds mentioned above. The crash found was a reproducible crash and the information on the vulnerability has been submitted to huntr.dev to inform the developers of the program. With more work and time put into this campaign, we could provide a more detailed analysis on the vulnerability and provide a solution for it. Bachelor of Engineering (Computer Science) 2022-04-19T08:26:30Z 2022-04-19T08:26:30Z 2022 Final Year Project (FYP) Ng, L. H. K. (2022). Finding instrumentable locations for fuzzing via static binary analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156539 https://hdl.handle.net/10356/156539 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Ng, Lyon Hong Kai
Finding instrumentable locations for fuzzing via static binary analysis
description Today, the exploitation of vulnerabilities which exists in every software program is still prevalent, leading to unintended repercussions. This highlights the importance of eradicating the pre-existing vulnerabilities before they can be exploited by hackers. In this study, American Fuzzy Lop Plus Plus (AFL++) was the fuzzer used to fuzz programs on the ubuntu system. The objective of this project is to find crashes that might lead to the discovery of vulnerabilities which were not documented before. The input files (seeds) consisted of mp4 files and binary files which were obtained from go-fuzz-corpus seed bank, as well as from submitted Proof-of-Concept (POC) files by other users. This paper provides a detailed explanation and highlights the steps for the fuzzing campaign done through a period of 10-12 months on the Program Under Test (PUT) with the seeds mentioned above. The crash found was a reproducible crash and the information on the vulnerability has been submitted to huntr.dev to inform the developers of the program. With more work and time put into this campaign, we could provide a more detailed analysis on the vulnerability and provide a solution for it.
author2 Liu Yang
author_facet Liu Yang
Ng, Lyon Hong Kai
format Final Year Project
author Ng, Lyon Hong Kai
author_sort Ng, Lyon Hong Kai
title Finding instrumentable locations for fuzzing via static binary analysis
title_short Finding instrumentable locations for fuzzing via static binary analysis
title_full Finding instrumentable locations for fuzzing via static binary analysis
title_fullStr Finding instrumentable locations for fuzzing via static binary analysis
title_full_unstemmed Finding instrumentable locations for fuzzing via static binary analysis
title_sort finding instrumentable locations for fuzzing via static binary analysis
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156539
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