sql-injection-detection

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sql-injection-detection

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RNNs for sql-injection detection 🔍. built in python with tensorflow and keras

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## LLMs models for SQL injection detection.

The SQL injection detection problem is such a major and hard problem that made many researchers working for it for years. Many research papers was released about this problematic, that I analyzed some of them during the internship. This project can be just another idea for solving this major problem, it can be a good starting point for researchers to develop an even more sophisticated model that well detect SQL injections.

This project implements an anomaly detection model based on an AutoEncoder architecture with LSTM layers to capture long-term dependencies.

The objective is to detect whether an input represents an SQL injection or normal text.

The model was buil in Python, using `TensorFlow` library with the `Keras` API. Additional tools and libraries used are listed in the `requirements.txt` file.

![auto-encoder](https://raw.githubusercontent.com/yassermessahli/sql-injection-detection/main/utils/images/Autoencoders-graph.png?token=GHSAT0AAAAAACKFTUBMF5RBXWZOVOQMTGAEZXFUINA)

This project is part of my internship at [**IRIS**](https://iris.dz) in Setif, Algeria, supervised by my professor at [**ESTIN**](https://www.estin.dz), Bejaia, Algeria.

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#### How to Use

1. Clone the repository or download the project files.
2. Install Python and the required dependencies listed in the `requirements.txt` file.
3. Navigate to the `./utils/scripts/` directory.
4. Run the `test.py` file.

You can also explore the model class in the `prediction.py` file.

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**Note:** This project is for general purposes. No data from ***IRIS*** or ***ESTIN*** is included in this repository.

**Next Steps:** A detailed report containing the full specifications of the project will be released soon.

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