{"id":19589713,"url":"https://github.com/jackaduma/nlp4cybersecurity","last_synced_at":"2025-10-24T05:21:33.934Z","repository":{"id":72237104,"uuid":"489583562","full_name":"jackaduma/NLP4CyberSecurity","owner":"jackaduma","description":"NLP  model and tech  for cyber security tasks","archived":false,"fork":false,"pushed_at":"2023-03-22T12:09:41.000Z","size":94164,"stargazers_count":87,"open_issues_count":2,"forks_count":27,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-05T00:25:22.262Z","etag":null,"topics":["code-injection","command-injection","cross-site-scripting","cross-site-scripting-proof","cyber-security","cybersecurity","deep-learning","machine-learning","malicious-url-detection","network-security","nlp","nlp-deep-learning","nlp-machine-learning","password-strength","phishing-attacks","phishing-detection","sql-injection","text-classification","xss-injection"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jackaduma.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-05-07T05:58:59.000Z","updated_at":"2025-03-10T05:47:45.000Z","dependencies_parsed_at":"2023-05-31T10:30:51.168Z","dependency_job_id":null,"html_url":"https://github.com/jackaduma/NLP4CyberSecurity","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jackaduma%2FNLP4CyberSecurity","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jackaduma%2FNLP4CyberSecurity/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jackaduma%2FNLP4CyberSecurity/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jackaduma%2FNLP4CyberSecurity/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jackaduma","download_url":"https://codeload.github.com/jackaduma/NLP4CyberSecurity/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251138933,"owners_count":21541976,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["code-injection","command-injection","cross-site-scripting","cross-site-scripting-proof","cyber-security","cybersecurity","deep-learning","machine-learning","malicious-url-detection","network-security","nlp","nlp-deep-learning","nlp-machine-learning","password-strength","phishing-attacks","phishing-detection","sql-injection","text-classification","xss-injection"],"created_at":"2024-11-11T08:20:22.842Z","updated_at":"2025-10-24T05:21:33.914Z","avatar_url":"https://github.com/jackaduma.png","language":"Jupyter Notebook","funding_links":["https://paypal.me/jackaduma?locale.x=zh_XC"],"categories":[],"sub_categories":[],"readme":"# **NLP4CyberSecurity**\n\n\n[![standard-readme compliant](https://img.shields.io/badge/readme%20style-standard-brightgreen.svg?style=flat-square)](https://github.com/jackaduma/CycleGAN-VC2)\n[![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://paypal.me/jackaduma?locale.x=zh_XC)\n\n[**中文说明**](./README.zh-CN.md) | [**English**](./README.md)\n\n------\n\nThis code is  NLP  models and tech  implementation for **cyber security** task, driven by deep learning model, a nice work on **cyber security**.\n\n本项目使用自然语言处理（NLP）技术应用于网络安全领域，包括恶意软件检测、漏洞发现和威胁情报等方面。该项目基于Python编程语言和机器学习框架Scikit-learn、TensorFlow和Keras等，实现了一些常见的NLP技术，如文本预处理、特征提取、词嵌入、文本分类和主题建模等。通过对网络安全方面的文本数据进行处理和分析，该项目能够提高网络安全人员的工作效率和准确性，以及更好地发现网络安全威胁。此外，该项目还提供了一些用于网络安全的NLP数据集和预训练模型，方便其他研究人员和开发者使用。\n\n- [x] Dataset\n  - [x] weak password\n  - [x] xss injection\n  - [x] malicious url\n  - [x] phishing url\n- [x] Usage\n  - [x] Training\n  - [x] Example \n- [ ] Demo\n- [x] Reference\n\n------\n\n## **Update**\n\n------\n\n\n## **Table of Contents**\n\n- [**NLP4CyberSecurity**](#nlp4cybersecurity)\n  - [**Update**](#update)\n  - [**Table of Contents**](#table-of-contents)\n  - [**Requirement**](#requirement)\n  - [**Usage**](#usage)\n  - [**Weak Password Detection**](#weak-password-detection)\n    - [**Eval Result**](#eval-result)\n  - [**XSS Injection Detection**](#xss-injection-detection)\n    - [**simple nn model**](#simple-nn-model)\n    - [**simple cnn model**](#simple-cnn-model)\n    - [**simple lstm model**](#simple-lstm-model)\n  - [**Malicious URL Detection**](#malicious-url-detection)\n    - [**RNN**](#rnn)\n    - [**CNN**](#cnn)\n    - [**Conv LSTM**](#conv-lstm)\n  - [**Phishing URL Detection**](#phishing-url-detection)\n  - [**Demo**](#demo)\n  - [**Star-History**](#star-history)\n  - [**Reference**](#reference)\n  - [**Donation**](#donation)\n  - [**License**](#license)\n  \n------\n\n\n\n## **Requirement** \n\n```bash\npip install -r requirements.txt\n```\n## **Usage**\n\n\n---\n\n\n## [**Weak Password Detection**](./01_weak_password_detect.ipynb)\n\nweak password detection with machine learning\n\nweak-password/password-strength detection with machine learning; 弱密码检测；密码强度检测\n\n### **Eval Result**\n\n```\n\n              precision    recall  f1-score   support\n\n           0    0.94406   0.83240   0.88472      8920\n           1    0.96327   0.98971   0.97631     49652\n           2    0.99035   0.95400   0.97184      8392\n\n    accuracy                        0.96428     66964\n   macro avg    0.96589   0.92537   0.94429     66964\nweighted avg    0.96410   0.96428   0.96355     66964\n\n```\n\n\n---\n\n## [**XSS Injection Detection**](02_xss_injection_detect.ipynb)\n\nxss injection detection with machine learning\n\n### **simple nn model**\n\n```\nPrecision score is : 0.9764296754250387\nRecall score is : 0.9830772223302859\n```\n\n### **simple cnn model**\n\n```\nPrecision score is : 0.9948463825569871\nRecall score is : 0.9762692083252286\n```\n\n### **simple lstm model**\n\n```\nPrecision score is : 0.9980311084859225\nRecall score is : 0.9869548286604362\n```\n---\n\n## [**Malicious URL Detection**](03_malicious_url_detect.ipynb)\n\nmalicious url detection with machine learning\n\n### **RNN**\n\n```\nAccuracy Score is:  0.8655441478439425\nPrecision Score is : 0.8579050828418984\nRecall Score is : 0.8767578205075642\nF1 Score:  0.8672290036092299\nAUC Score:  0.8655252346603806\n```\n\n### **CNN**\n\n```\nAccuracy Score is:  0.8379671457905544\nPrecision Score is : 0.8431494883953082\nRecall Score is : 0.831085236357673\nF1 Score:  0.8370738958974254\nAUC Score:  0.8379787529437384\n```\n\n\n### **Conv LSTM**\n\n```\nAccuracy Score is:  0.9242505133470226\nPrecision Score is : 0.9288969917958068\nRecall Score is : 0.9191095076052642\nF1 Score:  0.92397733127254\nAUC Score:  0.9242591842604873\n```\n\n---\n\n## [**Phishing URL Detection**](04_phishing_url_detect.ipynb)\n\nphishing url detection with machine learning\n\n```\naccuracy: 0.9982\nModel Accuracy: 99.82%\n```\n\n```\n              precision    recall  f1-score   support\n\n           0    0.99790   0.99895   0.99843      1904\n           1    0.99866   0.99732   0.99799      1495\n\n    accuracy                        0.99823      3399\n   macro avg    0.99828   0.99814   0.99821      3399\nweighted avg    0.99824   0.99823   0.99823      3399\n\n```\n\n------\n\n\n## **Demo**\n\nSamples:\n\n```\n```\n\n------\n## **Star-History**\n\n![star-history](https://api.star-history.com/svg?repos=jackaduma/NLP4CyberSecurity\u0026type=Date \"star-history\")\n\n------\n\n## **Reference**\n\n------\n\n## **Donation**\nIf this project help you reduce time to develop, you can give me a cup of coffee :) \n\nAliPay(支付宝)\n\u003cdiv align=\"center\"\u003e\n\t\u003cimg src=\"./misc/ali_pay.png\" alt=\"ali_pay\" width=\"400\" /\u003e\n\u003c/div\u003e\n\nWechatPay(微信)\n\u003cdiv align=\"center\"\u003e\n    \u003cimg src=\"./misc/wechat_pay.png\" alt=\"wechat_pay\" width=\"400\" /\u003e\n\u003c/div\u003e\n\n[![paypal](https://www.paypalobjects.com/en_US/i/btn/btn_donateCC_LG.gif)](https://paypal.me/jackaduma?locale.x=zh_XC)\n\n------\n\n## **License**\n\n[MIT](LICENSE) © Kun\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjackaduma%2Fnlp4cybersecurity","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjackaduma%2Fnlp4cybersecurity","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjackaduma%2Fnlp4cybersecurity/lists"}