Challenge Overview

You are a machine learning engineer at a competing tech firm. At a recent conference, the lead developer from **Animatrix AI** boasted that their new animal classification model was **unbreakable** and could not be deceived. As a proof of concept, they have a public-facing demo running. Your manager has tasked you with a bit of competitive research: find a flaw in their model. Your goal is to subtly alter a common animal image, making their state-of-the-art system misidentify it completely, thereby exposing the vulnerability in their architecture. The target machine runs Ubuntu OS with the IP address **10.10.1.121**. The objective is to use the **panda.jpg** image to create an adversarial version that remains visually a panda but causes the Animatrix AI model to predict a different animal; upload the adversarial image to the web UI and retrieve the flag shown when the model is fooled.

What You Will Learn

  • Identifying exposed services and understanding how the AI-based web application functions.
  • Analyzing the behavior of models like MobileNet used for image classification.
  • Generating adversarial examples by applying gradient-based perturbations using TensorFlow.
  • Manipulating input data to deceive the model into producing incorrect predictions.
  • Demonstrating weaknesses in AI systems by successfully bypassing model accuracy and retrieving the hidden flag.

Program Curriculum

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