  Cybersecurity threats in Additive Manufacturing (AM) are an increasing
concern as AM adoption continues to grow. AM is now being used for parts in the
aerospace, transportation, and medical domains. Threat vectors which allow for
part compromise are particularly concerning, as any failure in these domains
would have life-threatening consequences. A major challenge to investigation of
AM part-compromises comes from the difficulty in evaluating and benchmarking
both identified threat vectors as well as methods for detecting adversarial
actions. In this work, we introduce a generalized platform for systematic
analysis of attacks against and defenses for 3D printers. Our "OFFRAMPS"
platform is based on the open-source 3D printer control board "RAMPS." OFFRAMPS
allows analysis, recording, and modification of all control signals and I/O for
a 3D printer. We show the efficacy of OFFRAMPS by presenting a series of case
studies based on several Trojans, including ones identified in the literature,
and show that OFFRAMPS can both emulate and detect these attacks, i.e., it can
both change and detect arbitrary changes to the g-code print commands.
