PinDown: Generalized Application Code Identification And Functional Component Analysis In RTOS-based Firmware

Master Thesis (2024)
Author(s)

D.A. Prinsze (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Georgios Smaragdakis – Graduation committee member (TU Delft - Cyber Security)

J.E.A.P. Decouchant – Graduation committee member (TU Delft - Data-Intensive Systems)

Alexios Voulimeneas – Mentor (TU Delft - Cyber Security)

Andrea Continella – Mentor (University of Twente)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
07-10-2024
Awarding Institution
Delft University of Technology
Programme
Computer Science | Cyber Security
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Small embedded devices are becoming more prevalent in the world with each passing year to improve our quality of life. However, as more devices are created, an increasing number of older devices are declared obsolete despite still being used. This results in an increasing amount of devices being vulnerable to exploitation due to a lack of security updates. Identifying these vulnerabilities manually without any system knowledge is an arduous task, and current state-of-the-art technologies do not perform generalized analysis in RTOS-based firmware. In this work, we present PinDown, an analysis framework that enables the automated identification of application code in RTOS-based firmware without requiring partial system knowledge. By identifying functions that modify the heap, we can identify RTOS components that can be leveraged to locate memory regions that host application code.

Files

MSc_Thesis_-_Final.pdf
(pdf | 2.66 Mb)
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