The main purpose of castellum is to handle data of test subjects. It is important to be able to read and write this data in various ways. We are also legally required to provide some specific forms of access, e.g. exporting or deleting all data on a single subject.

On the other hand, we are also required to handle this data very carefully. Among other things, we are required to split the data so that users can only ever access the parts of the data they really need.

The security measures outlined in this section are meant to only allow access where allowed and required.

Account restrictions

  • Users are automatically logged out on inactivity

  • User accounts expire on a set date

  • (Mandatory) Secure authentication


Most actions in castellum are protected by one or more permission. For easier handling, permissions are usually not assigned directly. Instead, they are collected into meaningful groups (aka Roles). Castellum comes with some pre-defined sample groups, but you can adapt them to your needs.

Note that the django framework automatically generates a lot of permissions. Only a few of them are actually used. The full list is:

  • studies.approve_study

  • studies.view_study

  • studies.change_study

  • studies.delete_study

  • studies.access_study

  • subjects.view_subject

  • subjects.change_subject

  • subjects.delete_subject

  • subjects.export_subject

  • recruitment.recruit

  • recruitment.conduct_study

  • recruitment.search_participations

  • recruitment.view_current_appointments

  • recruitment.change_appointments

  • castellum_auth.privacy_level_1

  • castellum_auth.privacy_level_2

Study membership

If a user is a member of a study, they automatically gain the special access_study permission in the context of that study. Study managers can also assign additional groups to study members that only apply in the context of the study.


By managing study memberships, study managers can escalate their own priviliges inside their studies. For example, they can allow themselves to see recruitment attributes of participants.

All studies need to be approved before they can start recruitment. The approver should check for suspicious settings before approving the study. However, for practical reasons all study settings (including memberships) can still be changed after the approval. Some organizations will even choose to allow study managers to approve their own studies.

Privacy levels

Every subject has a privacy level. A user is only allowed to access that subject if they have a sufficient privacy level themselves. For recruitment attributes, you can define separate privacy levels for read and write access. A user’s privacy level is controlled via the special permissions privacy_level_1 and privacy_level_2. The three levels (0-2) accord to the data security levels of the Max Planck Society.

Access to resources and general domains

Similar to how a study membership allows a user to access a specific study, users need to be authorized to access specific resources and general domains. This can only be done by administrators.

Data separation


We chose to split the data into three different categories:

  • Scientific data is handled outside of castellum. Castellum only provides the pseudonyms that are used to map this data to subjects.

  • Data relevant for recruitment is handled in castellum.

  • Contact data is also handled in castellum, but in a separate database to provide an additional barrier.

Security Considerations

The described architecture provides a clear structure for developers that should help avoiding critical data leaks. Even if an attacker is able to dump a whole table or even a whole database, this structure still limits the impact.

However, it is important to understand that the barrier between recruitment and contact data is not that high. Since castellum has full access to both, an attacker can also gain full access. Spreading the system across several databases on different servers or even in different organizations does not help much if there is still a single point of entry.


In order to allow analysing suspicious behavior, critical actions such as search, deletion, or login attempts are logged to a separate log file.