Table of Contents
This project is a final project within the framework of a bachelor's degree in software engineering. First, we performed model training using machine learning libraries so that we could identify queries: malicious queries / plain queries and then we developed a web-dashboard app that displays data about queries using the model we trained.
- Malicious queries are queries whose content may contain text that could harm the database (SQL injection).
- Plain queries are queries without malicious targets.
This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.
For training the model: (You can use our pre-trained model which is in the model folder)
pip install nltk==3.5
pip install pandas==1.0.5
pip install numpy==1.19.5
pip install tensorflow==2.5.0
pip install keras==2.6.0
pip install scikit-learn==0.23.1For running app.py file (dashboard application):
pip install nltk==3.5
pip install dash==0.30.0
pip install pandas==1.0.5
pip install tensorflow==2.5.0
pip install dash-bootstrap-components==1.0.0We recommend working with a conda virtual environment to install the libraries but this is at your discretion.
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Clone the repo
git clone https://github.com/dudi709/SQL-injection-Final-Project.git
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Install the packages above
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Run
app.py
When the application is running you can see it HERE.
Distributed under the MIT License. See LICENSE.txt for more information.
Dudi Biton - dudi709@gmail.com
Avihay Maman - avihaymaman1234@gmail.com
Project Link: Github