This commit is contained in:
2024-10-13 21:47:23 +02:00
parent 5d1ec4f974
commit 084b66fe0e
5 changed files with 72 additions and 0 deletions

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from PIL import Image
# Open the image
image = Image.open('alles_mit_flag.bmp')
# Split the image into Red, Green, and Blue channels
red, green, blue = image.split()
# Save each channel as a separate grayscale image
red.save('red_channel.bmp')
green.save('green_channel.bmp')
blue.save('blue_channel.bmp')
# Optionally, show the images
red.show()
green.show()
blue.show()

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import requests
from fake_useragent import UserAgent
# URL to brute force
url = "https://ctfd.labs.inf.fh-dortmund.de/ctfd-challenge-4"
# Create a UserAgent instance
ua = UserAgent()
# Default HTML content
default_response = """<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<title>User Agent Info</title>
<link rel="stylesheet" href="/ctfd-challenge-4/static/style.css">
</head>
<body>
<div class="container">
<h1>IBM Workstation Server</h1>
<p>Diese Seite bedient ausschließlich von IBM eingerichtete Geräte</p>
</div>
</body>
</html>"""
# Function to brute force headers
def brute_force_user_agent():
for _ in range(500000): # Adjust the range for the number of User-Agents you want to try
user_agent = ua.random # Generate a random User-Agent
headers = {
"User-Agent": user_agent
}
try:
response = requests.get(url, headers=headers)
if response.text.strip() != default_response.strip():
print(f"User-Agent '{user_agent}' gives a different response:")
print(response.text)
return
# else:
# print(f"Nope: '{user_agent}'")
except requests.exceptions.RequestException as e:
print(f"Error with User-Agent '{user_agent}': {e}")
if __name__ == "__main__":
brute_force_user_agent()

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import requests
import json
import pandas as pd
api_url = "https://overfast-api.tekrop.fr/heroes"
response = requests.get(api_url)
json_data = response.json()
with open('heroes.json', 'w') as outfile: json.dump(json_data, outfile)
df = pd.read_json(json.dumps(json_data))
csv_data = df.to_csv('csv_data.csv')