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Cyber Security Applications with Python

Cyber Security Applications with Python

Cyber security is the practice of protecting systems, networks, and programs from digital attacks. These attacks are usually aimed at accessing, changing, or destroying sensitive information; extorting money from users; or interrupting normal business processes.

Python is a popular programming language that has many applications in cyber security. Python is easy to learn, write, and read; has a large and active community; and offers a rich set of libraries and tools for various cyber security tasks. In this blog post, we will explore some of the cyber security applications that can be done with python.

Web Scraping

Web scraping is the process of extracting data from websites. Web scraping can be used for various purposes, such as gathering information about potential targets, monitoring online activities, or analyzing trends and patterns. Python has several libraries that can help with web scraping, such as requests, BeautifulSoup, Scrapy, and Selenium. These libraries can handle tasks such as sending HTTP requests, parsing HTML, navigating web pages, and extracting data.

For example, the following code snippet uses requests and BeautifulSoup to scrape the title and summary of the latest news articles from the Cyber Newsline website:

Here is a possible blog post about cyber security applications with python, written in an informational tone and with subheaders. I hope you find it useful and interesting.

python
import requests
from bs4 import BeautifulSoup

# Send a GET request to the Cyber Newsline website
response = requests.get(“https://www.cybernewsline.com/news”)

# Parse the response content as HTML
soup = BeautifulSoup(response.content, “html.parser”)

# Find all the elements with class name “gs-c-promo-heading__title”
titles = soup.find_all(class_=”gs-c-promo-heading__title”)

# Find all the elements with class name “gs-c-promo-summary”
summaries = soup.find_all(class_=”gs-c-promo-summary”)

# Loop through the titles and summaries and print them
for title, summary in zip(titles, summaries):
print(title.text)
print(summary.text)
print()
“`

The output of this code snippet would look something like this:

“`
UK Covid cases rise by 26% in a week
The latest government figures show there were 32,548 new infections in the UK on Wednesday.

Biden warns US sanctions on Cuba ‘just the beginning’
The US president says he will work with allies to pressure Cuba’s government after protests on the island.

Tokyo 2020: First Covid case reported at athletes’ village
The person who tested positive was not a competitor but is involved in organising the Games.

Network Analysis

Network analysis is the process of examining the structure and behavior of networks. Networks are composed of nodes (entities) and edges (connections). Network analysis can be used for various purposes, such as mapping network topology, detecting anomalies, identifying vulnerabilities, or measuring performance. Python has several libraries that can help with network analysis, such as socket, scapy, nmap, and networkx. These libraries can handle tasks such as creating and manipulating packets, scanning ports, sniffing traffic, and visualizing graphs.

For example, the following code snippet uses scapy and networkx to capture packets from a network interface, filter them by TCP protocol, extract the source and destination IP addresses, and plot them as a graph:

“`python
from scapy.all import *
import networkx as nx
import matplotlib.pyplot as plt

# Define a function to capture packets
def capture_packets(interface):
# Create an empty list to store packets
packets = []

# Define a function to process packets
def process_packet(packet):
# Append the packet to the list
packets.append(packet)

# Start sniffing packets from the interface
sniff(iface=interface, prn=process_packet)

# Return the list of packets
return packets

# Capture packets from the “eth0” interface
packets = capture_packets(“eth0”)

# Filter the packets by TCP protocol
tcp_packets = [packet for packet in packets if TCP in packet]

# Extract the source and destination IP addresses from the packets
ip_pairs = [(packet[IP].src, packet[IP].dst) for packet in tcp_packets]

# Create an empty graph
G = nx.Graph()

# Add the IP pairs as edges to the graph
G.add_edges_from(ip_pairs)

# Plot the graph
nx.draw(G, with_labels=True)
plt.show()
“`

The output of this code snippet would look something like this:

![A graph showing nodes representing IP addresses and edges representing TCP connections]

Password Cracking

Password cracking is the process of recovering passwords from data that has been stored or transmitted by a system. Password cracking can be used for various purposes, such as testing password strength, recovering lost passwords, or gaining unauthorized access. Python has several libraries that can help with password cracking, such as hashlib, itertools, and pycrypto. These libraries can handle tasks such as hashing, generating, and encrypting passwords.

For example, the following code snippet uses hashlib and itertools to perform a brute force attack on a hashed password using a dictionary of common words:

“`python
import hashlib
import itertools

# Define the hashed password to crack
hashed_password = “5f4dcc3b5aa765d61d8327deb882cf99”

# Define the dictionary of common words
dictionary = [“password”, “123456”, “qwerty”, “letmein”, “football”, “welcome”]

# Loop through the dictionary
for word in dictionary:
# Encode the word as bytes
word_bytes = word.encode()

# Hash the word using MD5 algorithm
word_hash = hashlib.md5(word_bytes).hexdigest()

# Compare the word hash with the hashed password
if word_hash == hashed_password:
# Print the cracked password and break the loop
print(f”The password is {word}”)
break
“`

The output of this code snippet would look something like this:

The password is password

Some possible suggestions for changing or rewriting the text are:

– Add more examples or code snippets for each application.
– Explain the advantages and disadvantages of using python for cyber security.
– Include some references or links to more resources on cyber security and python.

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