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https://github.com/JHUAPL/Beat-the-Machine
Reverse engineering basics in puzzle form
https://github.com/JHUAPL/Beat-the-Machine
Last synced: 3 months ago
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Reverse engineering basics in puzzle form
- Host: GitHub
- URL: https://github.com/JHUAPL/Beat-the-Machine
- Owner: JHUAPL
- Created: 2020-04-15T15:44:55.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-05-20T01:27:21.000Z (over 4 years ago)
- Last Synced: 2024-04-24T13:40:36.134Z (6 months ago)
- Size: 3.3 MB
- Stars: 174
- Watchers: 17
- Forks: 13
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-hacking-lists - JHUAPL/Beat-the-Machine - Reverse engineering basics in puzzle form (Others)
README
# Beat the Machine - Reverse Engineering Basics in Puzzle Form
Beat the Machine is a workshop designed to introduce students to concepts in software reverse engineering (binary, hexadecimal, disassembly) on paper, without the need for computer & software setup. Target audience is middle school-to-college students who have had programming exposure (some familiarity with binary and hexadecimal is encouraged).
## Mostly Optical Simple Instruction Set (MOSIS)
MOSIS is a simple 16-bit instruction set designed to be easily disassembled by hand, while still resembling a real-world architecture. Most instructions fields are a single nybble (4 bits, 1 hexadecimal digit) - making disassembly straightforward once the binary is converted to hexadecimal.## Exercise Worksheets
* *Easy* - Exercises contain binary, hexadecimal instructions, disassembly. Students analyze the disassembly to solve problems.
* *Medium* - Exercises contain binary, hexadecimal instructions. Students disassemble using instruction set documentation and analyze diassembly to solve problems.
* *Difficult* - Exercises contain binary. Students convert to hexadecimal, disassemble using instruction set documentation, and analyze disassembly to solve problems.## Authors
Formerly "n00b to l33t" by Maddie Stone & JHU/APL staff, Summer 2017
Updated and open-sourced Spring 2020 by JHU/APL staff## License
Beat the Machine is released under the [Creative Commons Attribution-NonCommercial-ShareAlike license](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).