Search for documents in a domain through Google. The objective is to extract metadata

Overview

Supported Python versions License

MetaFinder - Metadata search through Google

   _____               __             ___________ .__               .___                   
  /     \     ____   _/  |_  _____    \_   _____/ |__|   ____     __| _/   ____   _______  
 /  \ /  \  _/ __ \  \   __\ \__  \    |    __)   |  |  /    \   / __ |  _/ __ \  \_  __ \ 
/    Y    \ \  ___/   |  |    / __ \_  |     \    |  | |   |  \ / /_/ |  \  ___/   |  | \/ 
\____|__  /  \___  >  |__|   (____  /  \___  /    |__| |___|  / \____ |   \___  >  |__|    
        \/       \/               \/       \/               \/       \/       \/          
        
|_ Author: @JosueEncinar
|_ Description: Search for documents in a domain through Google. The objective is to extract metadata
|_ Usage: python3 metafinder.py -d domain.com -l 100 -o /tmp

Installation:

> pip3 install metafinder

Upgrades are also available using:

> pip3 install metafinder --upgrade

Usage

CLI

metafinder -d domain.com -l 20 -o folder [-t 10] [-v] 

Parameters:

  • d: Specifies the target domain.
  • l: Specify the maximum number of results to be searched.
  • o: Specify the path to save the report.
  • t: Optional. Used to configure the threads (4 by default).
  • v: Optional. It is used to display the results on the screen as well.

In Code

import metafinder.extractor as metadata_extractor

documents_limit = 5
domain = "target_domain"
data = metadata_extractor.extract_metadata_from_google_search(domain, documents_limit)
for k,v in data.items():
    print(f"{k}:")
    print(f"|_ URL: {v['url']}")
    for metadata,value in v['metadata'].items():
        print(f"|__ {metadata}: {value}")

document_name = "test.pdf"
try:
    metadata_file = metadata_extractor.extract_metadata_from_document(document_name)
    for k,v in metadata_file.items():
        print(f"{k}: {v}")
except FileNotFoundError:
    print("File not found")

Author

This project has been developed by:

Contributors

Disclaimer!

This Software has been developed for teaching purposes and for use with permission of a potential target. The author is not responsible for any illegitimate use.

Owner
Josué Encinar
Offensive Security Engineer
Josué Encinar
ConvBERT-Prod

ConvBERT 目录 0. 仓库结构 1. 简介 2. 数据集和复现精度 3. 准备数据与环境 3.1 准备环境 3.2 准备数据 3.3 准备模型 4. 开始使用 4.1 模型训练 4.2 模型评估 4.3 模型预测 5. 模型推理部署 5.1 基于Inference的推理 5.2 基于Serv

yujun 7 Apr 08, 2022
This repository collects together basic linguistic processing data for using dataset dumps from the Common Voice project

Common Voice Utils This repository collects together basic linguistic processing data for using dataset dumps from the Common Voice project. It aims t

Francis Tyers 40 Dec 20, 2022
🏖 Easy training and deployment of seq2seq models.

Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear

Axel Springer Ideas Engineering GmbH 231 Nov 18, 2022
NLPShala , the best IDE for all Natural language processing tasks.

The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.

Abhi 3 Aug 08, 2021
Image2pcl - Enter the metaverse with 2D image to 3D projections

Image2PCL Enter the metaverse with 2D image to 3D projections! This is an implem

Benjamin Ho 0 Feb 05, 2022
Translate U is capable of translating the text present in an image from one language to the other.

Translate U is capable of translating the text present in an image from one language to the other. The app uses OCR and Google translate to identify and translate across 80+ languages.

Neelanjan Manna 1 Dec 22, 2021
Pre-Training with Whole Word Masking for Chinese BERT

Pre-Training with Whole Word Masking for Chinese BERT

Yiming Cui 7.7k Dec 31, 2022
CorNet Correlation Networks for Extreme Multi-label Text Classification

CorNet Correlation Networks for Extreme Multi-label Text Classification Prerequisites python==3.6.3 pytorch==1.2.0 torchgpipe==0.0.5 click==7.0 ruamel

Guangxu Xun 38 Dec 31, 2022
Practical Machine Learning with Python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Dipanjan (DJ) Sarkar 2k Jan 08, 2023
List of GSoC organisations with number of times they have been selected.

Welcome to GSoC Organisation Frequency And Details 👋 List of GSoC organisations with number of times they have been selected, techonologies, topics,

Shivam Kumar Jha 41 Oct 01, 2022
A list of NLP(Natural Language Processing) tutorials built on Tensorflow 2.0.

A list of NLP(Natural Language Processing) tutorials built on Tensorflow 2.0.

Won Joon Yoo 335 Jan 04, 2023
Smart discord chatbot integrated with Dialogflow to manage different classrooms and assist in teaching!

smart-school-chatbot Smart discord chatbot integrated with Dialogflow to interact with students naturally and manage different classes in a school. De

Tom Huynh 5 Oct 24, 2022
ElasticBERT: A pre-trained model with multi-exit transformer architecture.

This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli

fastNLP 48 Dec 14, 2022
Question answering app is used to answer for a user given question from user given text.

Question answering app is used to answer for a user given question from user given text.It is created using HuggingFace's transformer pipeline and streamlit python packages.

Siva Prakash 3 Apr 05, 2022
STonKGs is a Sophisticated Transformer that can be jointly trained on biomedical text and knowledge graphs

STonKGs STonKGs is a Sophisticated Transformer that can be jointly trained on biomedical text and knowledge graphs. This multimodal Transformer combin

STonKGs 27 Aug 11, 2022
Switch spaces for knowledge graph embeddings

SwisE Switch spaces for knowledge graph embeddings. Requirements: python3 pytorch numpy tqdm Reproduce the results To reproduce the reported results,

Shuai Zhang 4 Dec 01, 2021
MEDIALpy: MEDIcal Abbreviations Lookup in Python

A small python package that allows the user to look up common medical abbreviations.

Aberystwyth Systems Biology 7 Nov 09, 2022
Translation to python of Chris Sims' optimization function

pycsminwel This is a locol minimization algorithm. Uses a quasi-Newton method with BFGS update of the estimated inverse hessian. It is robust against

Gustavo Amarante 1 Mar 21, 2022
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

12.9k Jan 07, 2023
A programming language with logic of Python, and syntax of all languages.

Pytov The idea was to take all well known syntaxes, and combine them into one programming language with many posabilities. Installation Install using

Yuval Rosen 14 Dec 07, 2022