This code belongs to an experiment presenting a new method to perform Inferential SQL Injections using the advantages offered by the Bernstein-Vazirani algorithm in a quantum device. It will examine the SQL vulnerability vector contained in WebGoat training tool, a vulnerable web application from OWASP's Broken Web Application Project showing a possible way for exploiting it by injecting boolean conditions and at the same time triggering the hidden secret string problem in which the Bernstein-Vazirani algorithm is applied.
For more reference on the experiment details please visit: https://www.linkedin.com/pulse/applying-quantum-bernsteinvazirani-algorithm-sql-fernando-vel%25C3%25A1zquez-/
To run this project from a terminal using jupyter notebook:
- Firstly, you need to convert the jupyter notebook file which is in the format .ipynb to .py format using the jupyter nbconvert tool.
jupyter nbconvert --to <output format> <input notebook>Whereas, the is the desired output format. And the is the jupyter notbook filename.
-
Verify whether .py file is created in your working directory.
-
Finally, you could run a jupyter notebook .ipynb file from command prompt using the converted .py file as shown below.
python MyFirstNotebook.pyIf you have any feedback, please reach out to us at [email protected]
-
🔭 I’m an offensive security passionate working at Red Hat
-
🔎 I’m currently learning more about Quantum Technologies
-
📖 I recently wrote a book on Offensive Quantum Computing. Available at Amazon!!
-
⚡ I publish articles on technology topics at Meer