Abdullah Baghuth (@0xCyberY)
github

0xCyberY

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  • Stars
    star
    198
  • Global Rank 124,207 (Top 5 %)
  • Followers 94
  • Following 27
  • Registered almost 7 years ago
  • Most used languages
    Python
         28.6 %
    C
         21.4 %
    HTML
         21.4 %
    C++
         7.1 %
    Java
         7.1 %
    Shell
         7.1 %
    Jupyter Notebook
         7.1 %
  • Location 🇮🇳 India
  • Country Total Rank 4,539
  • Country Ranking
    HTML
         218
    C
         2,316
    Shell
         3,449
    Python
         4,262

Top repositories

1

ehtk

Ethical Hacking Toolkit is a collection of tools, cheat sheets, and resources for Ethical hackers, Penetration Tester, and Security Researchers etc. It contains almost all tools mentioned in CEH, OSCP, eCPPT and PNPT
HTML
96
star
2

CVE-T4PDF

CVEs and Techniques used PDF as an attack vector.
41
star
3

Antivirus-Evasion-Py2exe

Simple python script to evade antiviruses on fully patched and updated Windows environments using a py2exe.
Python
17
star
4

Burp-Suite

This is writeup for Burp Suite room in tryhackme.com
HTML
14
star
5

0xcybery.github.io

portfolio
HTML
7
star
6

Linux-Commands

The most useful Linux commands!
4
star
7

Buffer-Overflow-Prep

Windows 7 VM with Immunity Debugger and Putty preinstalled.
Python
1
star
8

Matrix-Multiplication

This program will preform multiplication of two matrices in c
C
1
star
9

HackBar-extension

This is HackBar extension working perfectly with CyberFox browser.
1
star
10

Count-Character-in-a-String

This program will count the repetition of each character given in a string
Python
1
star
11

cap

script for searching PATH or parameters for any executables caps applied to them.
Shell
1
star
12

0xCyberY

Profile
1
star
13

Sequential-allocation

a C program to simulate Sequential file allocation strategy.
C
1
star
14

Black-Hat-Python-2nd-Edition

Python Programming for Hackers and Pentesters
Python
1
star
15

DFS

DFS algorithm A standard DFS implementation puts each vertex of the graph into one of two categories: Visited Not Visited The purpose of the algorithm is to mark each vertex as visited while avoiding cycles. The DFS algorithm works as follows: Start by putting any one of the graph's vertices on top of a stack. Take the top item of the stack and add it to the visited list. Create a list of that vertex's adjacent nodes. Add the ones which aren't in the visited list to the top of stack. Keep repeating steps 2 and 3 until the stack is empty.
C
1
star
16

canteen-management-system

The main objective of this project is to manage the details of canteen Employee ,Item, Stock and Sales . It manages all the information about the canteen customer and sales The object is totally built at administration end and thus only the administrator is guaranteed the access . The purpose of the project to build an application program to reduce the manual work for managing the Canteen , Employee, Customer and Items . It tracks all the details about the items , stock and sales
C++
1
star
17

QUIZ-USING-MULTITHREAD-

ABSTRACT Modern education system includes conducting various activities. Exams are the most traditional method among that. Even in that traditional method for testing knowledge of students, technology has made it easier. In all the fields such as government exams and many exams are conducted online. We built a program to conduct these tests. The main intention of this project is to build Quiz app using multithreading. This project makes use of multithreading and java swing concepts. The built app is user friendly, easy to use and very helpful in schools and universities.
Java
1
star
18

abdullah-baghuth-Machine-Learning-for-Data-Analysis-coursera

About this Course Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions.
Jupyter Notebook
1
star