PortSmash Hyper-Threading Vuln Steals Decrypt Keys

PortSmash Hyper-Threading Vuln Steals Decrypt Keys

A new side-channel vulnerability has been found called PortSmash that uses a timing attack that to steal info from other processes running in the same CPU core with SMT/hyper-threading enabled.

Utilizing this attack, researchers were able to steal the private decryption key from an OpenSSL thread running in the same core as their exploit.crypto

For those that dont know, SMT/Hyper-threading is when one physical CPU core is split into two virtual logical cores that can be used two run two separate process threads at once.

This method can increase performance as the two threads will utilize idle CPU resources more efficiently to execute instructions faster.

A side channel timing attack is when an attacker analyzes how fast a thread executes particular instructions and utilizes that info to work backwards to discover what data was used as input.

The PortSmash vulnerability was discovered by researchers Billy Bob Brumley, Sohaib ul Hassan, Cesar Pereida Garcia, and Nicola Tuveri from the Tampere University of Technology in Finland as well as Alejandro Cabrera Aldaya from the Universidad Tecnologica de la Habana CUJAE in Cuba.

An advisory was made to the OSS-Sec mailing list and their research has been submitted as a paper titled “Port Contention for Fun and Profit” as a IACR eprint, which is currently awaiting moderation before it’s released.

In an email with the researchers, Nicola Tuveri explained to us that port contention was used to measure how long it took OpenSSL to perform an operation.

Using these measurements, the researchers were able to work backwards to recover a private key.

“Shortly and simplifying, with SMT and two threads per core, a process running on one thread will have its own instructions and data, but will share some hardware resources with a process running on the colocated thread.

Instructions will be decoded independently in simpler micro-operations and pipe-lined in the CPU to the corresponding Execution Units. (Execution Units are the actual silicon areas that are specialized to handle specific operations: i.e, there are a few EU dedicated to integer additions/subtraction, separate ones for integer multiplication, other for floating point arithmetic, etc.)

Every core has a complete set of EUs to support the whole i