Add application file

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+# Load the trained model
+model = tf.keras.models.load_model("mnist_ctf_model.h5")
+
+# Class mapping (0-9 with class 8 replaced by "CTF")
+class_mapping = {0: '0', 1: '1', 2: '2', 3: 'FLAG{fh9d2f9}', 4: '4', 5: '5', 6: '6', 7: '7', 8: '3', 9: '9'}
+
+# Function to preprocess the input image
+def preprocess_image(image):
+    image = image.convert("L")  # Convert image to grayscale
+    image = image.resize((28, 28))  # Resize to MNIST size
+    image = np.array(image) / 255.0  # Normalize pixel values
+    image = np.expand_dims(image, axis=0)  # Add batch dimension
+    image = np.expand_dims(image, axis=-1)  # Add channel dimension
+    return image
+
+# Prediction function
+def predict(image):
+    # Preprocess the image
+    image = preprocess_image(image)
+    
+    # Get the model's raw prediction (logits)
+    logits = model.predict(image)
+    
+    # Convert logits to probabilities
+    probabilities = tf.nn.softmax(logits)
+    
+    # Get the predicted class index
+    predicted_class = np.argmax(probabilities)
+    
+    # Get the class name from the mapping
+    class_name = class_mapping[predicted_class]
+    
+    return class_name
+
+# Gradio interface
+iface = gr.Interface(
+    fn=predict,  # Function to call for prediction
+    inputs=gr.Image(type="pil", label="Upload an MNIST-like Image"),  # Input: Image upload
+    outputs=gr.Textbox(label="Predicted Class"),  # Output: Text showing predicted class
+    title="Vault Challenge 1 - FGSM",  # Title of the interface
+    description="Upload an image, and the model will predict the digit. Try to fool the model into predicting 'CTF' using FGSM!. tips: use any image from the MNIST dataset, ranging from 0-9, except for 3. The goal is to fool the mode into predicting the digit as a 3, and you will get the flag. Ajust the epsilon parameter ;) "
+)
+
+# Launch the Gradio interface
+iface.launch()

mnist_ctf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e15409bf99089ed7618afd9876fbe1a27205600e64b9afb92fec267c86832b31
+size 1167392