  AI-based systems leverage recent advances in the field of AI/ML by combining
traditional software systems with AI components. Applications are increasingly
being developed in this way. Software engineers can usually rely on a plethora
of supporting information on how to use and implement any given technology. For
AI-based systems, however, such information is scarce. Specifically, guidance
on how to securely design the architecture is not available to the extent as
for other systems. We present 16 architectural security guidelines for the
design of AI-based systems that were curated via a multi-vocal literature
review. The guidelines could support practitioners with actionable advice on
the secure development of AI-based systems. Further, we mapped the guidelines
to typical components of AI-based systems and observed a high coverage where 6
out of 8 generic components have at least one guideline associated to them.
