  Fingerprinters leverage the heterogeneity in hardware and software
configurations to extract a device fingerprint. Fingerprinting countermeasures
attempt to normalize these attributes such that they present a uniform
fingerprint across different devices or present different fingerprints for the
same device each time. We present Centauri, a Rowhammer fingerprinting approach
that can build a unique and stable fingerprints even across devices with
homogeneous or normalized/obfuscated hardware and software configurations. To
this end, Centauri leverages the process variation in the underlying
manufacturing process that gives rise to unique distributions of
Rowhammer-induced bit flips across different DRAM modules. Centauri's design
and implementation is able to overcome memory allocation constrains without
requiring root privileges. Our evaluation on a test bed of about one hundred
DRAM modules shows that system achieves 99.91% fingerprinting accuracy.
Centauri's fingerprints are also stable with daily experiments over a period of
10 days revealing no loss in fingerprinting accuracy. We show that Centauri is
efficient, taking as little as 9.92 seconds to extract a fingerprint. Centauri
is the first practical Rowhammer fingerprinting approach that is able to
extract unique and stable fingerprints efficiently and at-scale.
