Deep Spectre is a deep learning side channel privileged memory reader heavily based on the PoC found here. I've written a Medium post explaining the deep learning code and you can read more about Spectre in CVE-2017-5753 and CVE-2017-5715 or check out the whitepaper and Google Project Zero post.
The Python 3 C API is used to glue the PoC code to the Keras deep learning API. Thus, you'll have to compile and install a native module. Simply run:
python setup.py installAfter installing the packages listed in requirements.txt, start the program and you should see the results below
./spectre.py
Using TensorFlow backend.
Collecting training data...
Scaling data between 0-1...
Training deep model...
Train on 48000 samples, validate on 16000 samples
Epoch 1/10
48000/48000 [==============================] - 4s 83us/step - loss: 2.9168 - acc: 0.3363 - val_loss: 0.7985 - val_acc: 0.8276
Epoch 2/10
48000/48000 [==============================] - 4s 73us/step - loss: 0.4543 - acc: 0.9007 - val_loss: 0.3505 - val_acc: 0.9204
Epoch 3/10
48000/48000 [==============================] - 4s 75us/step - loss: 0.2802 - acc: 0.9367 - val_loss: 0.2825 - val_acc: 0.9335
Epoch 4/10
48000/48000 [==============================] - 3s 73us/step - loss: 0.2516 - acc: 0.9441 - val_loss: 0.2948 - val_acc: 0.9293
Epoch 5/10
48000/48000 [==============================] - 4s 73us/step - loss: 0.2368 - acc: 0.9451 - val_loss: 0.2640 - val_acc: 0.9361
Epoch 6/10
48000/48000 [==============================] - 4s 73us/step - loss: 0.2320 - acc: 0.9460 - val_loss: 0.2765 - val_acc: 0.9360
Epoch 7/10
48000/48000 [==============================] - 3s 73us/step - loss: 0.2405 - acc: 0.9458 - val_loss: 0.2588 - val_acc: 0.9376
Epoch 8/10
48000/48000 [==============================] - 4s 74us/step - loss: 0.2324 - acc: 0.9468 - val_loss: 0.2502 - val_acc: 0.9403
Epoch 9/10
48000/48000 [==============================] - 4s 73us/step - loss: 0.2269 - acc: 0.9474 - val_loss: 0.2452 - val_acc: 0.9408
Epoch 10/10
48000/48000 [==============================] - 3s 72us/step - loss: 0.2277 - acc: 0.9467 - val_loss: 0.2663 - val_acc: 0.9392
The secret message is: The Magic Words are Squeamish Ossifrage.MIT