Top 10 Open-Source Python Libraries Hackers can Use in 2022

Top 10 Open-Source Python Libraries Hackers can Use in 2022
Published on

Here are some of the top 10 Python libraries used for hacking to break into computer networks

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It's widely used in machine learning, data science, and web development. Apart from that, it is successfully used by hackers and cybersecurity departments for identifying a hole in the computer networks which compromise the security protocols. Python libraries are a collection of related modules. It contains bundles of code that can be used repeatedly in different programs for identifying security loopholes.

Python Programming makes a popular choice for security professionals, ethical hackers, and programmers. Hackers and cybersecurity professionals use python scripts for analyzing malware and identifying vulnerabilities, though there are some who write exploit programs using python libraries.  Ethical hacking happens when there are potential threats to computer networks and as a result, the security gets compromised with unidentified or illegal access to the systems.

Here are some of the top 10 Python libraries used for hacking and each one has its unique identification and function

1. Scapy: Scapy is a complete interactive packet manipulation tool written in Python by Philippe Biondi. The tool is used to manipulate network packets, helping with discovering networks, probing, tracing, routing, and scanning. It is a powerful Python-based interactive packet manipulation program and library.

2. Requests: The requests library is an incredibly useful and versatile tool for writing python scripts that require interaction with web services. This library helps one to allow HTTP requests to be more user-friendly and includes intuitive features such as automatic content decompression and decoding, connection timeouts, basic & digits authentication, etc.

3. IMpacket: IMpacket is a library that includes a collection of Python classes for working with network protocols. Its goal is to make tasks easier for programmers so that they can work under a framework while abiding by some custom protocols.

4. pwntools: pwntools is designed to facilitate rapid prototyping and development. Pwntools allows users to quickly create exploits for challenges in CTF competitions.

5. Cryptography: Cryptography is a library that helps with encryption as well as the description of sets of data. It includes both high-level recipes and low-level interfaces to common cryptographic algorithms such as symmetric ciphers, message digests, and key derivation functions.

6. python-nmap: Python-nmap library helps in using Nmap port scanner. Nmap helps to identify and discover hosts on networks and detects the version number, and application name functioning on remote devices.

7. Faker: Faker is a Python package that generates fake data. It can generate anything from names, phone numbers, and addresses to fake texts, XML documents, bibliography entries, etc.

8. Twisted: Twisted library provides an abstraction of the TCP protocol that makes it easy to write network clients and servers. It supports both synchronous and asynchronous networking paradigms.

9. pylibnet: Pylibnet is a python module for the libnet packet injection library. It provides a python API for libnet and provides functionality for sending packets, sniffing frames, and displaying libpcap traces. Libnet includes packet creation at the IP layer and at the link layer as well as a host of supplementary and complementary functionality.

10. RawSocketpy: Raw socket is a layer 2 Python libraries for communication using the MAC addresses only. It does not involve transmission control protocol or user datagram protocol.

Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

                                                                                                       _____________                                             

Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.

Related Stories

No stories found.
logo
Analytics Insight
www.analyticsinsight.net