<p>In the current tutorial, the black-box model is a neural network implemented with TensorFlow and its predictions (the labels) are used to train a substitute model (a copy of the black-box model). The substitute model is then used to craft adversarial examples that transfer to the black-box model.  </p>

<p>In your case, you would have to replace bbox_val in </p>

<pre><code>bbox_val = batch_eval(sess, [x], [bbox_preds], [x_sub_prev],
                        args=eval_params)[0]
</code></pre>

<p>by the predictions of your random forest on the numpy array of substitute training data <code>x_sub_prev</code>. </p>

<p>You can find more information about the attack implemented in this tutorial in the following paper: <a href="https://arxiv.org/abs/1602.02697" rel="nofollow noreferrer">https://arxiv.org/abs/1602.02697</a></p>
Random Forest Black Box with CleverHans
<p>I am new to this stuff and trying to attack Random Forest with Black Box FGSM (from clever hans)</p>

<p>But I'm not sure how to implement it. They've a <a href="https://github.com/tensorflow/cleverhans/blob/master/cleverhans_tutorials/mnist_blackbox.py" rel="nofollow noreferrer">blackbox example for Mnist data</a> but I dont understand where should I put my random forest and where should I attack. Any help would be appreciated.</p>