TakeInfoatNistforICS - Take Information in NIST NVD for ICS

Overview

Take Information in NIST NVD for ICS

This project developed with Python.

When you search in the NIST NVD data, you write a keyword which is explain your research.(https://nvd.nist.gov/vuln/search) After that, you see the vuln ID, description, Published time ,and CVSS severity (Version 2 and Version3) fields.

I use the BeautifulSoup library for taking this fileds. The library parse the htlm codes in web sites for what do you want to take. I write the results Sqlite database and json format.

I run the project with -w parameter. This parameter is that what dou you want the search in NIST NVD databse.

Screen Shot 2022-01-03 at 15 13 21

You can see the research results in the json and database files.

Screen Shot 2022-01-03 at 15 13 41

Screen Shot 2022-01-03 at 15 14 41

You can see the NVD result numbers are same with my results.

Screen Shot 2022-01-03 at 15 16 17

You can use this project in blue team opportunities. For example, you want to monitor which products have vulnerabilities. When the product has a new vulnerability, you will see this problem and take a solution.

I used this results for ICS Security. I developed this project at the National Testbed Center for Critical Infrastructures - CENTER SAU (https://center.sakarya.edu.tr). I developed another project called Asset Management in ICS Systems in there. I got ip addresses, mac addresses, vendor names, protocols, version numbers to identify ICS products. I used the vendor name keywords to submit to NVD databases. You can see "Siemens S7-1200" keyword results for monitoring in ELK Stack. If the product has a new CVE or vulnerability, I can monitor in the ELK Stack.

image

Python with OpenCV - MediaPip Framework Hand Detection

Python HandDetection Python with OpenCV - MediaPip Framework Hand Detection Explore the docs » Contact Me About The Project It is a Computer vision pa

2 Jan 07, 2022
[제 13회 투빅스 컨퍼런스] OK Mugle! - 장르부터 멜로디까지, Content-based Music Recommendation

Ok Mugle! 🎵 장르부터 멜로디까지, Content-based Music Recommendation 'Ok Mugle!'은 제13회 투빅스 컨퍼런스(2022.01.15)에서 진행한 음악 추천 프로젝트입니다. Description 📖 본 프로젝트에서는 Kakao

SeongBeomLEE 5 Oct 09, 2022
Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style disentanglement in image generation and translation" (ICCV 2021)

DiagonalGAN Official Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Trans

32 Dec 06, 2022
When BERT Plays the Lottery, All Tickets Are Winning

When BERT Plays the Lottery, All Tickets Are Winning Large Transformer-based models were shown to be reducible to a smaller number of self-attention h

Sai 16 Nov 10, 2022
Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al.

nam-pytorch Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al. [abs, pdf] Installation You can access nam-pytorch vi

Rishabh Anand 11 Mar 14, 2022
Code for the Paper "Diffusion Models for Handwriting Generation"

Code for the Paper "Diffusion Models for Handwriting Generation"

62 Dec 21, 2022
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

Taehoon Kim 2.6k Dec 31, 2022
Implementation of Wasserstein adversarial attacks.

Stronger and Faster Wasserstein Adversarial Attacks Code for Stronger and Faster Wasserstein Adversarial Attacks, appeared in ICML 2020. This reposito

21 Oct 06, 2022
The code for paper Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation Algorithm

Quantum Qubit Rotation Algorithm Single qubit rotation gates $$ U(\Theta)=\bigotimes_{i=1}^n R_x (\phi_i) $$ QQRA for the max-cut problem This code wa

SheffieldWang 0 Oct 18, 2021
ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation

ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya

Lihe Yang 147 Jan 03, 2023
A PyTorch-based library for fast prototyping and sharing of deep neural network models.

A PyTorch-based library for fast prototyping and sharing of deep neural network models.

78 Jan 03, 2023
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Namkyeong Lee 59 Dec 01, 2022
The implemention of Video Depth Estimation by Fusing Flow-to-Depth Proposals

Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,

32 Jun 14, 2022
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"

SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P

Gi-Cheon Kang 9 Jul 05, 2022
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

benfour 16 Sep 28, 2022
Official implementation of "Articulation Aware Canonical Surface Mapping"

Articulation-Aware Canonical Surface Mapping Nilesh Kulkarni, Abhinav Gupta, David F. Fouhey, Shubham Tulsiani Paper Project Page Requirements Python

Nilesh Kulkarni 56 Dec 16, 2022
Object DGCNN and DETR3D, Our implementations are built on top of MMdetection3D.

This repo contains the implementations of Object DGCNN (https://arxiv.org/abs/2110.06923) and DETR3D (https://arxiv.org/abs/2110.06922). Our implementations are built on top of MMdetection3D.

Wang, Yue 539 Jan 07, 2023
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.

The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio

NAVER 23 Oct 09, 2022
A Repository of Community-Driven Natural Instructions

A Repository of Community-Driven Natural Instructions TLDR; this repository maintains a community effort to create a large collection of tasks and the

AI2 244 Jan 04, 2023
tmm_fast is a lightweight package to speed up optical planar multilayer thin-film device computation.

tmm_fast tmm_fast or transfer-matrix-method_fast is a lightweight package to speed up optical planar multilayer thin-film device computation. It is es

26 Dec 11, 2022