Welcome to my comprehensive course on python programming and ethical hacking. The course assumes you have NO prior knowledge in any of these topics, and by the end of it you'll be at a high intermediate level being able to combine both of these skills to write python programs to hack into computer systems exactly the same way that black hat hackers do. That's not all, you'll also be able to use the programming skills you learn to write any program even if it has nothing to do with hacking. This course is highly practical but it won't neglect the theory, we'll start with basics of ethical hacking and python programming and installing the needed software. Then we'll dive and start programming straight away. You'll learn everything by example, by writing useful hacking programs, no boring dry programming lectures. The course is divided into a number of sections, each aims to achieve a specific goal, the goal is usually to hack into a certain system! We'll start by learning how this system work and its weaknesses, then you'll lean how to write a python program to exploit these weaknesses and hack the system. As we write the program I will teach you python programming from scratch covering one topic at a time. By the end of the course you're going to have a number of ethical hacking programs written by yourself (see below) from backdoors, keyloggers, credential harvesters, network hacking tools, website hacking tools and the list goes on. You'll also have a deep understanding on how computer systems work, how to model problems, design an algorithm to solve problems and implement the solution using python. As mentioned in this course you will learn both ethical hacking and programming at the same time, here are some of the topics that will be covered in the course: Programming topics: Writing programs for python 2 and 3. Using modules and libraries. Variables, types ...etc. Handling user input. Reading and writing files. Functions. Loops. Data structures. Regex. Desiccation making. Recursion. Threading. Object oriented programming. Packet manipulation using scapy. Netfilterqueue. Socket programming. String manipulation. Exceptions. Serialisation. Compiling programs to binary executables. Sending & receiving HTTP requests. Parsing HTML. + more! Hacking topics: Basics of network hacking / penetration testing. Changing MAC address & bypassing filtering. Network mapping. ARP Spoofing - redirect the flow of packets in a network. DNS Spoofing - redirect requests from one website to another. Spying on any client connected to the network - see usernames, passwords, visited urls ....etc. Inject code in pages loaded by any computer connected to the same network. Replace files on the fly as they get downloaded by any computer on the same network. Detect ARP spoofing attacks. Bypass HTTPS. Create malware for Windows, OS X and Linux. Create trojans for Windows, OS X and Linux. Hack Windows, OS X and Linux using custom backdoor. Bypass Anti-Virus programs. Use fake login prompt to steal credentials. Display fake updates. Use own keylogger to spy on everything typed on a Windows & Linux. Learn the basics of website hacking / penetration testing. Discover subdomains. Discover hidden files and directories in a website. Run wordlist attacks to guess login information. Discover and exploit XSS vulnerabilities. Discover weaknesses in websites using own vulnerability scanner. Programs you'll build in this course: You'll learn all the above by implementing the following hacking programs mac_changer - changes MAC Address to anything we want. network_scanner - scans network and discovers the IP and MAC address of all connected clients. arp_spoofer - runs an arp spoofing attack to redirect the flow of packets in the network allowing us to intercept data. packet_sniffer - filters intercepted data and shows usernames, passwords, visited links ....etc dns_spoofer - redirects DNS requests, eg: redirects requests to from one domain to another. file_interceptor - replaces intercepted files with any file we want. code_injector - injects code in intercepted HTML pages. arpspoof_detector - detects ARP spoofing attacks. execute_command payload - executes a system command on the computer it gets executed on. execute_and_report payload - executes a system command and reports result via email. download_and_execute payload - downloads a file and executes it on target system. download_execute_and_report payload - downloads a file, executes it, and reports result by email. reverse_backdoor - gives remote control over the system it gets executed on, allows us to Access file system. Execute system commands. Download & upload files keylogger - records key-strikes and sends them to us by email. crawler - discovers hidden paths on a target website. discover_subdomains - discovers subdomains on target website. spider - maps the whole target website and discovers all files, directories and links. guess_login - runs a wordlist attack to guess login information. vulnerability_scanner - scans a target website for weaknesses and produces a report with all findings. As you build the above you'll learn: Setting up a penetration testing lab to practice hacking safely. Installing Kali Linux and Windows as virtual machines inside ANY operating system. Linux Basics. Linux terminal basics. How networks work. How clients communicate in a network. Address Resolution Protocol - ARP. Network layers. Domain Name System - DNS. Hypertext Transfer Protocol - HTTP. HTTPS. How anti-virus programs work. Sockets. Connecting devices over TCP. Transferring data over TCP. How website work. GET & POST requests. And more! By the end of the course you're going to have programming skills to write any program even if it has nothing to do with hacking, but you'll learn programming by programming hacking tools! With this course you'll get 24/7 support, so if you have any questions you can post them in the Q&A section and we'll respond to you within 15 hours. Notes: This course is created for educational purposes only and all the attacks are launched in my own lab or against devices that I have permission to test. This course is totally a product of Zaid Sabih & zSecurity, no other organisation is associated with it or a certification exam. Although, you will receive a Course Completion Certification from Udemy, apart from that NO OTHER ORGANISATION IS INVOLVED. What you’ll learn 170+ videos on Python programming & ethical hacking Install hacking lab & needed software (on Windows, OS X and Linux) Learn 2 topics at the same time - Python programming & Ethical Hacking Start from 0 up to a high-intermediate level Write over 20 ethical hacking and security programs Learn by example, by writing exciting programs Model problems, design solutions & implement them using Python Write programs in Python 2 and 3 Write cross platform programs that work on Windows, OS X & Linux Have a deep understanding on how computer systems work Have a strong base & use the skills learned to write any program even if its not related to hacking Understand what is Hacking, what is Programming, and why are they related Design a testing lab to practice hacking & programming safely Interact & use Linux terminal Understand what MAC address is & how to change it Write a python program to change MAC address Use Python modules and libraries Understand Object Oriented Programming Write object oriented programs Model & design extendable programs Write a program to discover devices connected to the same network Read, analyse & manipulate network packets Understand & interact with different network layers such as ARP, DNS, HTTP ....etc Write a program to redirect the flow of packets in a network (arp spoofer) Write a packet sniffer to filter interesting data such as usernames and passwords Write a program to redirect DNS requests (DNS Spoofer) Intercept and modify network packets on the fly Write a program to replace downloads requested by any computer on the network Analyse & modify HTTP requests and responses Inject code in HTML pages loaded by any computer on the same network Downgrade HTTPS to HTTP Write a program to detect ARP Spoofing attacks Write payloads to download a file, execute command, download & execute, download execute & report .....etc Use sockets to send data over TCP Send data reliably over TCP Write client-server programs Write a backdoor that works on Windows, OS X and Linux Implement cool features in the backdoor such as file system access, upload and download files and persistence Write a remote keylogger that can register all keystrikes and send them by Email Interact with files using python (read, write & modify) Convert python programs to binary executables that work on Windows, OS X and Linux Convert malware to torjans that work and function like other file types like an image or a PDF Bypass Anti-Virus Programs Understand how websites work, the technologies used and how to test them for weaknesses Send requests towebsites and analyse responses Write a program that can discover hidden paths in a website Write a program that can map a website and discover all links, subdomains, files and directories Extract and submit forms from python Run dictionary attacks and guess login information on login pages Analyse HTML using Python Interact with websites using Python Write a program that can discover vulnerabilities in websites Are there any course requirements or prerequisites? Basic IT knowledge No Linux, programming or hacking knowledge required. Computer with a minimum of 4GB ram/memory Operating System: Windows / OS X / Linux Who this course is for: Anybody interested in learning Python programming Anybody interested in learning ethical hacking / penetration testing Instructor User photo Zaid Sabih Ethical Hacker, Computer Scientist & CEO of zSecurity My name is Zaid Al-Quraishi, I am an ethical hacker, a computer scientist, and the founder and CEO of zSecurity. I just love hacking and breaking the rules, but don’t get me wrong as I said I am an ethical hacker. I have tremendous experience in ethical hacking, I started making video tutorials back in 2009 in an ethical hacking community (iSecuri1ty), I also worked as a pentester for the same company. In 2013 I started teaching my first course live and online, this course received amazing feedback which motivated me to publish it on Udemy. This course became the most popular and the top paid course in Udemy for almost a year, this motivated me to make more courses, now I have a number of ethical hacking courses, each focusing on a specific field, dominating the ethical hacking topic on Udemy. Now I have more than 350,000 students on Udemy and other teaching platforms such as StackSocial, StackSkills and zSecurity. Instructor User photo z Security Leading provider of ethical hacking and cyber security training, zSecurity is a leading provider of ethical hacking and cyber security training, we teach hacking and security to help people become ethical hackers so they can test and secure systems from black-hat hackers. Becoming an ethical hacker is simple but not easy, there are many resources online but lots of them are wrong and outdated, not only that but it is hard to stay up to date even if you already have a background in cyber security. Our goal is to educate people and increase awareness by exposing methods used by real black-hat hackers and show how to secure systems from these hackers. Video course

学习正则表达式

A hands-on simulation of attacking a vulnerable login page using Python. This repo includes a Flask-based vulnerable login page and Python scripts to exploit weaknesses in regex validation and brute-force login attempts. Perfect for learning web penetration testing basics and ethical hacking techniques.

A puzzle game where you try to get a secure password. Useful for learning RegEx

Regular Expression Matching Can Be Simple And Fast

The purpouse this repository is to maintain some python common regex examples

Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing. Regex for pattern searching, Stemming and lemmatization, Part of Speech tagging to auto process raw text files, Named Entity Recognition, Topic Modelling etc

This is a simple regex parsing router made as an exercise in learning.

Mixed neural network / fuzzy similarity based phrase database matching. Uses universal sentence embeddings from Tensorflow combined with KNN and fuzzy similarity to perform slot filling based on a list of potential phrases. The approach allows for one shot learning and the efficiency will be determined by KNN (or other approximate nearest neighbor). The name "PhraseX" comes from "Regex", as it is a more flexible way of matching phrases than using regex and better suited for natural language.

Regexcellence is a community driven platform for learning regex.

Personal learning notes about regexm, scraped and revised from https://github.com/ziishaned/learn-regex/blob/master/translations/README-cn.md. Will continue to update if necessary.

ML (Machine Learning)/NLP project for extraction of Names, Aadhar ID, PAN numbers. It uses Pytesseract OCR for extracting text from images, and uses Hugging Face NER model for Name extraction and regex library for extracting PAN and Aadhaar ID numbers.

Mongo db console commands //showing the existing dbs.. show dbs //use test switching to db test, (only creating it when actually adding new data) //prompts the name of the working db now db //the fllw would prompt the count(), in the link2 collection, in the current db... >db.links2.count() //inserting a record in links2 db.links2.insert({title:"unn titulo", url:"", comment:"", tags:["un primer tag", "un segundo tag"], saved_on: new Date}) //working with an object the javascript way... data = {} | data.title = "un titulo" | data.tags = ["un tag", "otro"] | data.meta = {} | data.meta.OS = "win7" | db.links2.insert(data) //printing the result of the find, in the structured json format. db.links2.find().forEach(printjson) //--> in this case we pass to forEach the printjson function... //retriving only the first of the results of the find method. db.links2.find()[0] db.links2.find()[0]._id //getting the timestamp present in the _id variable (is made of (also) the time it was created) db.links2.find()[0]._id.getTimestamp() /*the following function creates, when called, a new collection inside the same working db, that tracks the last id number we are in. This allows having the same behavieur than in relational DBs.*/ //apparently, u have to declare this function... function counter(name) { var ret = db.counter.findAndModify({query:{_id:name}, update:{$inc:{next:1}}, "new":true, upsert:true}); return ret.next; } //so u can do something like db.products.insert({_id:counter("products"), nombre:"primer nombre"}) //the result is something like: { "_id": 1, "name": "un producto" } { "_id": 2, "name": "otro producto" } /*referencing in MongoDB*/ db.users.insert({name:"Richard"}) var a = db.users.findOne({name:"Richard"}) db.links2.insert({title:"primer titulo", author:a._id}) //reference to other collection throught the _id key... //quering db.users.findOne({ _id:link.author }) //a way to make manual inner joins... within the user db, we search for a coincidence of our _ids on the links2 db, author field. ---note--- embedding is much more efficient when we have significantly more read than writes. Otherwise, consider using the normalized way. These depends on every case. /**/ #importing data from a .js in json format. With mongod running or in a services: > ../../../mongodb/bin/mongo 127.0.0.1/bookmarks bookmarks.js //the first part is the location to the mongo exe in the mongo usual location //the second part is the server and db in which we will be importing in //the third part is the file with all the mongo commands... --this bookmarks file is in C:\Tuto\mongo\trying -- https://raw.github.com/tuts-premium/learning-mongodb/master/08%20-%20bookmarks.js /*bookmarks.js extract*/ var u1 = db.users.findOne({ 'name.first': 'John' }), u2 = db.users.findOne({ 'name.first': 'Jane' }), u3 = db.users.findOne({ 'name.first': 'Bob' }); db.links.insert({ title: 'Nettuts+', url: 'http://net.tutsplus.com', comment: 'Great site for web dev tutorials', tags: ['tutorials', 'dev', 'code'], favourites: 100, userId: u1._id }); /**/ //connecting directly to db bookmarks > ../../../mongodb/bin/mongo bookmarks //searching in the collection all docs that have inside the tags array the "code" element. //this can be done because we are dealing with an array --> array advantages... db.users.find({tags:"code"}).forEach(printjson) //with findOne u can do (not with find) findOne().name db.links.find({favourites:100}, title:true, url:1) //selecting only some fields... db.links.find({favourites:100}, tags:0) //selecting all but the tag field... //selecting inside an object... db.users.findOne({"name.first": "John"}) db.users.findOne({"name.first": "John"}, "name.last":1) var john = db.users.findOne({"name.first": "John"}) db.links.find({userId:john._id}, {title:1, _id: 0}) /*queries directives*/ //greater than 150 db.links.find({favourites:{$gt:150}}, {_id:0, favourites:1, title:1}).forEach(printjson) db.links.find({favourites:{$gt:150}}, {_id:0, favourites:1, title:1}).count() //less than db.links.find({favourites:{$lt:150}}, {_id:0, favourites:1, title:1}).forEach(printjson) //$lte, $gte -- and iqual //using in db.users.find({"name.first":{$in:["John", "Jane"]}}) //the opposite is $nin db.users.find({"name.first":{$nin:["John", "Jane"]}}) //$all -- only the records with all the specifications in "tags" field. db.links.find({tags: {$all:["code", "marketplace"]}}, {title:1, tags:1, _id:0}) //$ne -- not equal //the $or flag search for the fullfillment of at least one of the elements in the array passed... db.users.find({$or: [{"name.first": "John"}, {"name.last": "Wilson"}]}) //the opposite: $nor //inclusive: $and //$exists db.users.find({email: {$exists: true}}) //$mod db.links.find({favourites: {$mod: [5, 0]}}, {_id:0, title:1, favourites:1}) db.links.find({favourites: {$not: {$mod: [5, 0]}}}, {_id:0, title:1, favourites:1}) //elemMatch -- inside logins, search for an element match that has minutes = 20, and return the complete record db.users.find({logins: {$elemMatch: {minutes: 20}}}) //searching for an 'at' prior to 2012/03/30.. and returning the whole record... db.users.find({logins: {$elemMatch: {at: { $lt: new Date(2012, 3, 30)}}}}) //using where -- c) is equivalent to a) a) db.users.find({ $where: 'this.name.first === "John"'}) b) db.users.find({ $where: 'this.name.first === "John"', age:30}) c) db.users.find( 'this.name.first === "John"') //injecting functions in mongodb -- as this example returns trueéfalse, its going to return values randomly var frand = function() {return Math.random() > 0.5} db.users.find(frand) // var f = function() { return this.name.first === "John"} db.users.find(f) //or db.users.find( {$where: f} ) //other queries //distinct -- returns a list of diff results db.links.distinct('favourites') --> [100, 32, 21, 78, ...] db.links.distinct("url") db.links.group({ key:{userId : true}, initial:{favCount: 0}, reduce: function (doc, o) {o.favCount += doc.favourites}, finalize: function(o) {o.name = db.users.findOne({ _id: o.userId}).name } }); *** //the final part is not working... db.links.group({ key:{userId : true}, initial:{favCount: 0}, reduce: function (doc, o) {o.favCount += doc.favourites} }); db.links.group({ key:{userId : true}, initial:{favCount: 0}, reduce: function (doc, o) {o.favCount += doc.favourites}, finalize: function(o) {o.name = "richard"}} ); //regex db.links.find({ title: /tuts\+$/}) db.links.find({ title: {regex: /tuts\+$/}}, {title:1}) //counting db.users.count({'name.first': 'John'}) db.users.count(); //all users in the collection //sorting, limit db.links.find({}, {title:1}).sort({title:1}).limit(1) //1: asc -1: desc //sorting, skipping and limiting... normal behavieur in the pagination rutine... db.links.find({}, {title:1, _id:0}).sort({title:1}).skip(3).limit(3) /*updating*/ //by replacement or by modification... ---general form /* db.collection.update( <query>, <update>, { upsert: <Boolean>, //if not found insert multi: <Boolean>, //change in all the condition <query> is fullfilled } ) */ // more info in http://docs.mongodb.org/manual/reference/method/db.collection.update/ db.users.update({-the query object-}, {-the update object-}, -upsert boolean-); var n = {title:"Nettuts+"} db.links.find(n, {title:1}) db.links.update(n, {$inc: {favourites: 5}}) var q = {"name.last": "Doe"} db.users.find(q, {name:1}) //we can use set to update a field or add a completly new one... db.users.update(q, {$set: {"name.last": "Doetix"}}) //modifying an existing field.. db.users.update(q, {$set: {"email": "doetix81@gmail.com"}}) //inserting a new one... //to remove a field w use unset db.users.update(q, {$unset: {job: "Web developper"}}) db.users.update({"name.first":"John"}, {$set: {job:"Web developer"}}, false, true) //modifying and then inserting an object var bob = db.users.findOne({"name.first":"Bob"}) >bob { "_id" : ObjectId("525f06242df9763abe646b62"), "name" : { "first" : "Bob", "last" : "Smith" }, "age" : 31, "email" : "bob.smith@gmail.com", "passwordHash" : "last_password_hash" } > bob.job = "Thick Brush Painter" > db.users.save(bob) //find and modify -- findAndModify {{}} /* The findAndModify command atomically modifies and returns a single document. By default, the returned document does not include the modifications made on the update. To return the document with the modifications made on the update, use the new option. { findAndModify: <string>, query: <document>, sort: <document>, remove: <boolean>, //one of | update: <document>, //this two | new: <boolean>, //if the new object must be shown or the old one.. fields: <document>, //fields to show in the result upsert: <boolean> } */ > db.links.findAndModify({ query:{favourites: {$gt:150}}, sort:{title:1}, update:{favourites: 333}, new: true, fields: {_id:0} }); //pulling into arrays db.links.update(n, { $push: {tags: "jobs"}}) > db.links.findOne(n).tags //several... db.links.update(n, {$pushAll:{tags: ['blogs','press','contests']}}) //on pull into the array if the new element is not present.. db.links.update(n, {$addToSet:{tags: "dev"}}) //doing the same with an array... db.links.update(n, {$addToSet:{ tags:{$each: ["dev", "interviews"]} }}) //pulling out content from the array... db.links.update(n, {$pull: {tags:'interviews'}}) //pulling several... db.links.update(n, {$pullAll: {tags: ['blogs','dev', 'contests']}}) //poping out from the beginning or the end.. db.links.update(n, {$pop: {tags: 1}}) //--from the end (-1 -- from the beginning) //positional operator... only the subobject gets updated... db.users.update({'logins.minutes': 20} , {$inc:{ 'logins.$.minutes': 10}}, false, true) db.users.update({'logins.minutes': 20} , {$set:{ 'logins.$.location': 10}}, false, true) db.users.update({'logins.minutes': 30}, {$set: {random: true}}, false, true) //renaming the fields name... db.links.update({url: {$exists: true}}, {$rename:{"url": "camino"}}, false, true); //more info on the positional operator in: http://docs.mongodb.org/manual/reference/operator/update/positional/ //taken from there: /* The positional $ operator facilitates updates to arrays that contain embedded documents. Use the positional $ operator to access the fields in the embedded documents with the dot notation on the $ operator. db.collection.update( { <query selector> }, { <update operator>: { "array.$.field" : value } } ) */ /***EXAMPLE Consider the following document in the students collection whose grades field value is an array of embedded documents: { "_id" : 4, "grades" : [ { grade: 80, mean: 75, std: 8 }, { grade: 85, mean: 90, std: 5 }, { grade: 90, mean: 85, std: 3 } ] } Use the positional $ operator to update the value of the std field in the embedded document with the grade of 85: db.students.update( { _id: 4, "grades.grade": 85 }, { $set: { "grades.$.std" : 6 } } ) ***/ //removing db.users.remove({'name.first': "John"}) //all the collections in the selected db... show collections //dropping completly a collection... db.acoll.drop() //indexes... db.links.find().explain db.links.ensureIndex({ title: 1}) //in ascending order.. in mainly important in cpompund indexes.. //a reflect of this index can be found in that db indexes collection db.system.indexes.find(); //u cound put an index to a canging value, but every time u change that value the index must be updated. keep in mind. //usually is a good idea to set the indexes at the beginning when no data is present in the collections. However, u could use the following formula to treat duplicates and unique data //keeping only the first one, deleting the others.. db.links.ensureIndex({ title: 1}, { unique: true, dropDups: true}) //when considering the case of some of the documents without the idexed field, to save mongo from storing space for this index if the field itself has not been inserted: db.links.ensureIndex({ title: 1}, {sparse: true}) //its important to think of the compund index as a nested one, an index of an index. Its related to each problem-case. Like in the case of the recepies: indexing first the ingredient and the the recepie, makes more sense than indexing in reverse. Its all related on how u are going to search. db.links.ensureIndex({ title: 1, url: 1}) //this one means that u can search on title; or on title and url... db.links.ensureIndex({ a: 1, b: 1, c: 1}) //searches are possible on a; a, b; a, b, c //deleting indexes db.links.dropIndex("title_1"); //the same way that appears in system.index collection... /*concepts to follow*/ //Sharding and Replica Set... http://www.slideshare.net/Dataversity/common-mongodb-use-cases-13695677 http://docs.mongodb.org/ecosystem/use-cases/product-catalog/ db.collection.update({"grades.grade":80}, { $set: {"grades.$.std": 18}})

Interactive CLI tool for learning and sharpening your Regex skills

Examples based regex learning

Learning RegEx for validation new user sign up using HTML, CSS & Javascript

Best regex practices for learning regex

No description available

A TypeScript port of regular expression engine described at https://codezine.jp/article/detail/3039

Main Project. Machine Learning/Web Scraping/Regex

Real-time phishing URL detection system using machine learning, regex patterns, and domain analysis. Built with Python and Streamlit for interactive web-based security assessment.

POC project to explore the processing of structured(invoices, legal documents) as well as unstructured documents(handwritten prescriptions, notes) to extract relevant fields and related information. Python is used for implementation. Possible solutions involving: Deep Learning/Computer Vision/NLP/Regex.

In this repo, I shared my project in advanced python with Jadi Mirmirani in Maktabkhooneh which ended on April 24, 2020. In this project, which was done on https://ihome.ir/ we used bs4, MySQL, sklearn and regex, first of all, we stored the information and price of each property in a database, and then with the Machine Learning algorithm, we tried to predict the price of the property desired by the user. You can get the price by entering the type and information about the property you want.

gamification for learning regex

No description available

like it says on the tin

learning regex

Learning regex

Regex practice repository featuring multiple real-world patterns with live JavaScript validation demos.

No description available