Website fingerprinting enables a local eavesdropper to determine which websites a user is visiting over an encrypted connection and can even reveal information sent over the Tor anonymity system. In this work, we present Deep Fingerprinting (DF), a new website fingerprinting attack against Tor that leverages a type of deep learning called Convolutional Neural Networks (CNN). The DF attack attains over 98% accuracy on Tor traffic and can even defeat some recently proposed defenses against website fingerprinting. The success of this attack shows the value of deep learning techniques in security applications.