# PositiveTechnologies/seq2seq-web-attack-detection

<https://repo.masters-masters.com/en/repos/PositiveTechnologies/seq2seq-web-attack-detection>

[Home](https://repo.masters-masters.com/en) › [PositiveTechnologies](https://repo.masters-masters.com/en/owners/PositiveTechnologies) › [seq2seq-web-attack-detection](https://repo.masters-masters.com/en/repos/PositiveTechnologies/seq2seq-web-attack-detection)

PositiveTechnologies/seq2seq-web-attack-detection has 157 stars on GitHub. Its RepoMasters card: Prototype tier. The implementation of the Seq2Seq model for…

| Field | Value |
| --- | --- |
| Owner | [PositiveTechnologies](https://repo.masters-masters.com/en/owners/PositiveTechnologies) |
| Stars | 157 |
| Forks | 56 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2018 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [PositiveTechnologies/seq2seq-web-attack-detection](https://github.com/PositiveTechnologies/seq2seq-web-attack-detection) |

## Repository

The implementation of the Seq2Seq model for web attack detection. The Seq2Seq model is usually used in Neural Machine Translation. The main goal of this project is to demonstrate the relevance of the NLP approach for web security.

Archived: this repository is read-only

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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