Regularly, hackers steal data sets containing user identifiers and passwords. Often these data sets become publicly available. The most prominent and important leaks use bad password protection mechanisms, e.g. rely on unsalted password hashes, despite longtime known recommendations. The accumulation of leaked password data sets allows the research community to study the problems of password strength estimation, password breaking and to conduct usability and usage studies. The impact of these leaks in terms of privacy has not been studied. In this paper, we consider attackers trying to break the privacy of users,while not breaking a single password. We consider attacks revealing that distinct identifiers are in fact used by the same physical person. We evaluate large scale linkability attacks based on properties and relations between identifiers and password information. With these attacks, stronger passwords lead to better predictions. Using a leaked and publicly available data set containing 130106 encrypted passwords, we show that a privacy attacker is able to build a database containing the multiple identifiers of people, including their secret identifiers. We illustrate potential consequences by showing that a privacy attacker is capable of deanonymizing (potentially embarrassing) secret identifiers by intersecting several leaked password databases.