Code analysis and rewriting for data debloating and improved fuzz testing

Code rewriting has predominantly been used for the purposes of improving security and reducing code bloat in software. This research explores the applicability of code rewriting in the contexts of data-based debloating [IOSPReD] and in enhancing fuzz testing [TOPr]. IOSPReD focuses on reducing the amount of data that is included with an application to the extent of its requirement. To this end, IOSPReD automatically tracks and packages only necessary data chunks along with its application, in a container. In particular, a reduced datastore is generated and the underlying I/O calls in the program are rewritten via I/O specialization to access the reduced data accurately. TOPr focuses on target-oriented pruning to reduce the exploration space during code execution. TOPr eliminates unnecessary code that do not lead to specific target locations. Specifically, the program code is rewritten to redirect control flow only towards paths leading to the target location. In an attempt to improve fuzz testing towards predefined target locations in code, we integrate TOPr with a popularly used directed fuzzer, AFLGo.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Niddodi, Chaitra Prasad

Contributors dc:contributor

• Mohan, Sibin
• Marinov, Darko
• Misailovic, Sasa
• Rilee, Michael Lee

• Code Rewriting
• Data Debloating
• Fuzz Testing

Statement dc:rights

• Copyright 2023 Chaitra Prasad Niddodi

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/121205

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F121205