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[DeadFace CTF] - Price Check

Posted Oct 20, 2024
By Teiiko
2 min read


DEADFACE has been hacking random people all over town and no one can seem to figure out what they are doing. All we know at this time is that the most recent site that was hit was Otto’s Grocery Store. Oddly, only the customers are being affected and not the company’s network. What is happening? They hired our firm to sniff out the attack and we successfully captured a strange file being sent across the guest WiFi. We believe this is the primary attack vector, and we’ve heard some victims mention that they had to “scan” something - maybe it is in the wrong format? Can you figure out how this file is being used in the attack to reveal the flag?

Submit the flag as flag{flag_text_here}



Table of contents:



Given File

We are given the following .csv file:

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We notice here several lines containing the values ​​0 or 255. These values ​​of 0 and 255 are typically used to represent black and white pixels in binary images. We can then try to convert this data into an image in order to visualize what it could represent.

Python Implementation

Here, we will use matplotlib library.

The Matplotlib library in Python is used to create data visualizations. It can generate various types of charts, such as line charts, histograms, bar charts, pie charts, scatter charts, etc.

We will also use NumPy which is essential for manipulating tables (or matrices) of digital data.

The first step therefore consists of first recovering our values ​​0 and 255 then storing them in an array before being able to manipulate them.

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data = np.array([
    [0,255,255,255,255,255,255,0,255,255,255,255,0,255,0,0,255,255,0,0,255,0,255,255,255,0,0,255,255],
    [255,0,0,0,0,0,255,0,0,0,255,255,0,0,255,0,255,255,0,0,255,255,255,255,0,255,0,255,255],
    [255,0,255,255,255,0,255,0,0,0,255,0,0,0,0,255,0,0,0,255,0,255,0,0,0,255,0,255,255],
    [0,0,255,255,255,0,255,0,0,255,0,255,0,0,255,255,255,0,0,0,255,255,0,255,255,255,255,255,255],
    [255,0,255,255,255,0,255,0,255,255,255,255,0,255,0,255,255,255,0,255,255,255,255,255,255,255,0,255,255],
    [0,0,0,0,0,0,255,0,0,255,255,255,0,255,0,255,0,255,255,255,255,0,0,0,255,255,0,0,255],
    [255,255,255,255,255,255,255,0,255,0,255,0,0,255,255,255,0,255,0,0,255,0,255,0,255,0,0,0,255],
    [255,0,0,0,0,0,0,0,255,255,0,0,255,0,0,0,0,0,255,0,255,0,0,0,255,255,0,0,0],
    [0,255,0,255,255,255,255,0,0,0,255,255,0,255,255,255,0,255,0,0,255,255,255,255,255,255,0,255,255],
    [0,0,255,0,255,255,0,0,0,0,0,0,255,0,255,0,0,255,0,255,255,0,0,0,255,255,0,255,0],
    [255,0,0,255,0,255,255,0,0,255,255,0,255,0,0,0,255,255,255,0,255,0,0,0,255,0,0,0,0],
    [255,255,255,255,0,255,0,0,0,255,255,255,255,255,255,0,255,255,255,0,0,255,0,255,255,0,255,0,255],
    [255,0,0,255,0,0,255,255,255,0,0,255,0,255,0,0,0,255,0,255,255,255,0,255,0,0,0,255,0],
    [255,255,0,255,255,255,0,0,0,0,0,255,0,255,0,255,255,255,0,255,255,255,255,0,0,255,0,255,255],
    [255,0,0,255,255,0,255,255,0,255,255,0,0,255,255,255,0,255,255,0,0,0,0,0,255,255,255,0,0],
    [255,0,0,255,255,255,0,255,0,0,0,255,255,0,0,0,0,255,255,0,0,0,255,255,255,255,0,0,255],
    [0,0,255,255,255,0,255,0,255,0,255,255,255,255,255,255,255,255,0,0,255,255,0,0,0,0,0,0,255],
    [255,0,255,0,255,255,0,255,0,255,255,255,0,0,255,0,0,255,255,0,0,255,255,255,255,255,0,0,0],
    [255,0,0,0,255,0,255,0,255,255,255,255,255,0,0,0,255,0,255,0,255,0,0,0,0,255,255,0,0],
    [255,0,255,255,0,0,0,255,255,0,0,255,0,255,255,0,255,255,255,0,0,0,255,255,255,0,255,0,255],
    [255,0,0,0,255,0,255,255,255,255,255,0,0,255,0,0,0,255,0,255,0,255,255,255,255,255,0,0,255],
    [0,0,0,0,0,0,0,0,255,0,0,0,0,255,0,255,255,255,0,255,255,0,0,0,0,0,0,0,0],
    [255,255,255,255,255,255,255,0,255,0,255,0,255,0,255,0,255,0,255,0,255,0,255,255,255,255,255,255,255],
    [255,0,0,0,0,0,255,0,255,255,0,255,255,0,0,0,255,0,0,255,255,0,255,0,0,0,0,0,255],
    [255,0,255,255,255,0,255,0,255,0,255,0,0,0,0,0,0,0,255,0,0,0,255,0,255,255,255,0,255],
    [255,0,255,255,255,0,255,0,255,0,255,255,255,0,0,0,0,0,255,0,0,0,255,0,255,255,255,0,255],
    [255,0,255,255,255,0,255,0,0,0,255,0,255,0,255,0,0,255,255,0,255,0,255,0,255,255,255,0,255],
    [255,0,0,0,0,0,255,0,0,255,255,0,255,255,255,255,0,255,0,255,0,0,255,0,0,0,0,0,255],
    [255,255,255,255,255,255,255,0,255,0,0,0,255,255,255,0,255,255,0,255,0,0,255,255,255,255,255,255,255]
])

Then, we just have to reconstruct the image with matplotlib.

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plt.imshow(data, cmap='gray', vmin=0, vmax=255)
plt.axis('off')
plt.gca().set_aspect('equal', adjustable='box')
plt.show()

Which gives us the following final script:

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import numpy as np
import matplotlib.pyplot as plt

data = np.array([
    [0,255,255,255,255,255,255,0,255,255,255,255,0,255,0,0,255,255,0,0,255,0,255,255,255,0,0,255,255],
    [255,0,0,0,0,0,255,0,0,0,255,255,0,0,255,0,255,255,0,0,255,255,255,255,0,255,0,255,255],
    [255,0,255,255,255,0,255,0,0,0,255,0,0,0,0,255,0,0,0,255,0,255,0,0,0,255,0,255,255],
    [0,0,255,255,255,0,255,0,0,255,0,255,0,0,255,255,255,0,0,0,255,255,0,255,255,255,255,255,255],
    [255,0,255,255,255,0,255,0,255,255,255,255,0,255,0,255,255,255,0,255,255,255,255,255,255,255,0,255,255],
    [0,0,0,0,0,0,255,0,0,255,255,255,0,255,0,255,0,255,255,255,255,0,0,0,255,255,0,0,255],
    [255,255,255,255,255,255,255,0,255,0,255,0,0,255,255,255,0,255,0,0,255,0,255,0,255,0,0,0,255],
    [255,0,0,0,0,0,0,0,255,255,0,0,255,0,0,0,0,0,255,0,255,0,0,0,255,255,0,0,0],
    [0,255,0,255,255,255,255,0,0,0,255,255,0,255,255,255,0,255,0,0,255,255,255,255,255,255,0,255,255],
    [0,0,255,0,255,255,0,0,0,0,0,0,255,0,255,0,0,255,0,255,255,0,0,0,255,255,0,255,0],
    [255,0,0,255,0,255,255,0,0,255,255,0,255,0,0,0,255,255,255,0,255,0,0,0,255,0,0,0,0],
    [255,255,255,255,0,255,0,0,0,255,255,255,255,255,255,0,255,255,255,0,0,255,0,255,255,0,255,0,255],
    [255,0,0,255,0,0,255,255,255,0,0,255,0,255,0,0,0,255,0,255,255,255,0,255,0,0,0,255,0],
    [255,255,0,255,255,255,0,0,0,0,0,255,0,255,0,255,255,255,0,255,255,255,255,0,0,255,0,255,255],
    [255,0,0,255,255,0,255,255,0,255,255,0,0,255,255,255,0,255,255,0,0,0,0,0,255,255,255,0,0],
    [255,0,0,255,255,255,0,255,0,0,0,255,255,0,0,0,0,255,255,0,0,0,255,255,255,255,0,0,255],
    [0,0,255,255,255,0,255,0,255,0,255,255,255,255,255,255,255,255,0,0,255,255,0,0,0,0,0,0,255],
    [255,0,255,0,255,255,0,255,0,255,255,255,0,0,255,0,0,255,255,0,0,255,255,255,255,255,0,0,0],
    [255,0,0,0,255,0,255,0,255,255,255,255,255,0,0,0,255,0,255,0,255,0,0,0,0,255,255,0,0],
    [255,0,255,255,0,0,0,255,255,0,0,255,0,255,255,0,255,255,255,0,0,0,255,255,255,0,255,0,255],
    [255,0,0,0,255,0,255,255,255,255,255,0,0,255,0,0,0,255,0,255,0,255,255,255,255,255,0,0,255],
    [0,0,0,0,0,0,0,0,255,0,0,0,0,255,0,255,255,255,0,255,255,0,0,0,0,0,0,0,0],
    [255,255,255,255,255,255,255,0,255,0,255,0,255,0,255,0,255,0,255,0,255,0,255,255,255,255,255,255,255],
    [255,0,0,0,0,0,255,0,255,255,0,255,255,0,0,0,255,0,0,255,255,0,255,0,0,0,0,0,255],
    [255,0,255,255,255,0,255,0,255,0,255,0,0,0,0,0,0,0,255,0,0,0,255,0,255,255,255,0,255],
    [255,0,255,255,255,0,255,0,255,0,255,255,255,0,0,0,0,0,255,0,0,0,255,0,255,255,255,0,255],
    [255,0,255,255,255,0,255,0,0,0,255,0,255,0,255,0,0,255,255,0,255,0,255,0,255,255,255,0,255],
    [255,0,0,0,0,0,255,0,0,255,255,0,255,255,255,255,0,255,0,255,0,0,255,0,0,0,0,0,255],
    [255,255,255,255,255,255,255,0,255,0,0,0,255,255,255,0,255,255,0,255,0,0,255,255,255,255,255,255,255]
])


plt.imshow(data, cmap='gray', vmin=0, vmax=255)
plt.axis('off')
plt.gca().set_aspect('equal', adjustable='box')
plt.show()

After execution we obtained this QR Code:

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All we have to do is read it and we get: flag{that_will_be_five_dollars}

🚩 flag{that_will_be_five_dollars}

Thanks for reading !

writeups
Steganography Python DeadFace CTF
This post is licensed under CC BY 4.0 by the author.
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