Malware sandbox systems have become a critical part of the Internet’s defensive infrastructure. These systems allow malware researchers to quickly understand a sample’s behavior and effect on a system. However, current systems face two limitations: first, for performance reasons, the amount of data they can collect is limited (typically to system call traces and memory snapshots). Second, they lack the ability to perform retrospective analysis—that is, to later extract features of the malware’s execution that were not considered relevant when the sample was originally executed. In this paper, we introduce a new malware sandbox system, Malrec, which uses whole-system deterministic record and replay to capture high-fidelity, whole-system traces of malware executions with low time and space overheads. We demonstrate the usefulness of this system by presenting a new dataset of 66,301 malware recordings collected over a two-year period, along with two preliminary analyses that would not be possible without full traces: an analysis of kernel mode malware and exploits, and a fine-grained malware family classification based on textual memory access contents. The Malrec system and dataset can help provide a standardized benchmark for evaluating the performance of future dynamic analyses.