The Netcap (NETwork CAPture) framework efficiently converts a stream of network packets into platform neutral type-safe structured audit records that represent specific protocols or custom abstractions. These audit records can be stored on disk or exchanged over the network, and are well suited as a data source for machine learning algorithms. Since parsing of untrusted input can be dangerous and network data is potentially malicious, a programming language that provides a garbage collected memory safe runtime is used for the implementation. It was developed for a series of experiments in a bachelor thesis on the implementation and evaluation of secure and scalable anomaly-based network intrusion detection. Slides from the presentation at the Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities are available on researchgate. The project won the 2nd Place at Kaspersky Labs SecurIT Cup 2018 in Budapest. Netcap uses Google's Protocol Buffers to encode its output, which allows accessing it across a wide range of programming languages. Alternatively, output can be emitted as comma separated values, which is a common input format for data analysis tools and systems.