Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77138
Title: American fuzzy lop (AFL) fuzzing
Authors: Goh, Brandon Wen Heng
Keywords: DRNTU::Science::Mathematics
Issue Date: 2019
Abstract: This final year project introduces the concept of fuzzing to discover flaws in code, and expose loopholes that might have the potential to cause damage to computer systems. Fuzzing is a fairly new method of discovering bugs within programs that might not otherwise be easily caught using traditional methods such as source code analysis and limited testing using a set of pre-defined inputs. Attempts will be made to discover bugs by testing the extraction function from the open-source software archiver 7-Zip. The fuzzer American Fuzzy Lop (AFL) will be employed for this project. AFL employs a novel type of compile-time instrumentation and genetic algorithms to generate semi-valid data and increase code coverage, reducing effort and time required to find potential exploitable vulnerabilities. Debugging will form the second half of this paper by detailing how faults can be identified within the application. The paper will conclude by listing of problems found in the paper and possible remediations that could be performed to improve the reliability of 7-Zip.
URI: http://hdl.handle.net/10356/77138
Schools: School of Physical and Mathematical Sciences 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP.pdf
  Restricted Access
FYP Thesis1.71 MBAdobe PDFView/Open

Page view(s) 5

1,150
Updated on May 7, 2025

Download(s) 50

84
Updated on May 7, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.