# foolme - misc
> Can you fool me?>> nc 202.112.51.176 9999>> (FLAG format: BCTF{})>> [Download Attachments](./c08be7bc-c68e-4c18-8372-f3167c92fc97.zip)
This is a challenge that receives a base64 encoded image, compares it to areference image, and if they are similar enough, sends both the submitted imageand reference image through the [Inception image classifier neural network](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/inception.py).If the images are classified as different objects, you get the flag.
The first similarity comparison is a simple bytewise difference comparisonbetween the raw RGB data of the images. The threshold is width\*height\*bytes_per_pixel\*3,which with the 299\*299\*3 size of the reference image gives us a minimum of3143 bytes - over 1000 pixels that can be fully changed. In practice, a lotmore, since the minimum only happens when a pixel changes from pure white topure black.
So, what kind of things might be confusing for a neural network? I thoughtabout projects like [CV Dazzle](https://cvdazzle.com/) which camouflagesfaces with bright colors and hard lines, and decided to just paint a couple ofthin lines in high contrast across the image:
![not a flower](./edited.jpg)
I saved the image, ensuring that JPEG quality was 100% avoid recompressionnoise that could trigger the threshold, and uploaded it. And it worked - gotthe flag!