  In June 2016, Apple announced that it will deploy differential privacy for
some user data collection in order to ensure privacy of user data, even from
Apple. The details of Apple's approach remained sparse. Although several
patents have since appeared hinting at the algorithms that may be used to
achieve differential privacy, they did not include a precise explanation of the
approach taken to privacy parameter choice. Such choice and the overall
approach to privacy budget use and management are key questions for
understanding the privacy protections provided by any deployment of
differential privacy.
  In this work, through a combination of experiments, static and dynamic code
analysis of macOS Sierra (Version 10.12) implementation, we shed light on the
choices Apple made for privacy budget management. We discover and describe
Apple's set-up for differentially private data processing, including the
overall data pipeline, the parameters used for differentially private
perturbation of each piece of data, and the frequency with which such data is
sent to Apple's servers.
  We find that although Apple's deployment ensures that the (differential)
privacy loss per each datum submitted to its servers is $1$ or $2$, the overall
privacy loss permitted by the system is significantly higher, as high as $16$
per day for the four initially announced applications of Emojis, New words,
Deeplinks and Lookup Hints. Furthermore, Apple renews the privacy budget
available every day, which leads to a possible privacy loss of 16 times the
number of days since user opt-in to differentially private data collection for
those four applications.
  We advocate that in order to claim the full benefits of differentially
private data collection, Apple must give full transparency of its
implementation, enable user choice in areas related to privacy loss, and set
meaningful defaults on the privacy loss permitted.
