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README.md

Heist ML CTF Challenges

In this web application challenge, the 🕵️ security researcher needs to compromise CityPolice's AI cameras and secure a smooth escape for Heist crews red getaway car 🚗 after the heist.

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Setup 🛠️

✋ ❗ ❗ Challenge can be either installed via docker as docker image (Step1a) OR via native installation (Step1b) 🚫

👉 Step 1a - Building Docker Image of the Application To Host The Challenge

clone the repo using git clone https://github.com/alexdevassy/Machine_Learning_CTF_Challenges.git

cd Machine_Learning_CTF_Challenges\Heist_ML_CTF_Challenge/

docker build -t heist_ml_ctf .

To run the challenge docker run --rm -p 5000:5000 heist_ml_ctf

OR

👉 Step 1b - Setting Up Python Flask App To Host The Challenge

The challenge works best with Python 3.10.11

Create virtual enviornment in python using python -m venv virtualspace

In windows, activate the virtual enviornemnt with .\virtualspace\Scripts\activate

In ubuntu, activate the virtual enviornemnt with source /virtualspace/bin/activate

git clone https://github.com/alexdevassy/Machine_Learning_CTF_Challenges.git

cd Machine_Learning_CTF_Challenges/Heist_ML_CTF_Challenge/

pip install -r .\requirements.txt

python app.py

Now the CTF Home Page 🏡 can be accessed in host systems browser at http://127.0.0.1:5000/CTFHomePage. Read 👓 through the page and click on "Start Challenge" to start the CTF.

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Rules 📐 & Clues 🧐

Dont peak into app.py. Everything you need to conquer this CTF is neatly tucked away in the web application itself. 😁 In case if the application throws unexpected errors or behaves in weird way, use 'Reset' button to reset the CTF challene to its initial state.

For solution to CTF challenge visit : Heist_CTF_Solution

🚫 A quick heads-up: The video below is contains CTF solution spoilers 😅. So, if you're still up for the challenge and enjoy a bit of mystery, it might be best to steer clear of this one.

Heist_ML_CTF_Challenge.mp4