Timing Analysis of Keystrokes and Timing Attacks on SSH

SSH is designed to provide a secure channel between two hosts. Despite the encryption and authentication mechanisms it uses, SSH has two weakness: First, the transmitted packets are padded only to an eight-byte boundary (if a block cipher is in use), which reveals the approximate size of the original data. Second, in interactive mode, every individual keystroke that a user types is sent to the remote machine in a separate IP packet immediately after the key is pressed, which leaks the interkeystroke timing information of users’ typing. In this paper, we show how these seemingly minor weaknesses result in serious security risks. First we show that even very simple statistical techniques suffice to reveal sensitive information such as the length of users’ passwords or even root passwords. More importantly, we further show that by using more advanced statistical techniques on timing information collected from the network, the eavesdropper can learn significant information about what users type in SSH sessions. In particular, we perform a statistical study of users’ typing patterns and show that these patterns reveal information about the keys typed. By developing a Hidden Markov Model and our key sequence prediction algorithm, we can predict key sequences from the interkeystroke timings. We further develop an attacker system, Herbivore , which tries to learn users’ passwords by monitoring SSH sessions. By collecting timing information on the network, Herbivore can speed up exhaustive search for passwords by a factor of 50. We also propose some countermeasures. In general our results apply not only to SSH, but also to a general class of protocols for encrypting interactive traffic. We show that timing leaks open a new set of security risks, and hence caution must be taken when designing this type of protocol. This research was supported in part by the Defense Advanced Research Projects Agency under DARPA contract N6601-99-28913 (under supervision of the Space and Naval Warfare Systems Center San Diego) and by the National Science foundation under grants FD9979852 and CCR-0093337.