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This repository contains code to generate a dataset that can be used to train machine learning models for software fault injection.

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software-fault-injection

This repository contains code to generate a dataset that can be used to train supervised machine learning models to detect instruction-level software fault injection for any software executable.

Usage

python3 chaosduck.py --filename NovaHomeDaemon_Ext --arch arm --fault_list 'nop' 'flp'

--filename - file name of the software executable to inject faults.

--arch - arch or x86 - hardware architecture for which the software executable was created.

--fault_list - list of faults to inject in the software executable. Example - 'nop' 'flp' 'jmp' 'none'

More information on usage and details to follow soon.

Acknowledgement

This tool uses the uses Chaos Duck tool (developed by Igor Zavalyshyn) to inject faults into the software executable.

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This repository contains code to generate a dataset that can be used to train machine learning models for software fault injection.

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