A simulation pipeline is the linked set of tools, assets, and data used to test a system in a virtual environment before it is deployed in the real world. In robotics and Physical AI, this can include scene generation, physics engines, synthetic data creation, model evaluation, and export into training or runtime systems.
It matters in cyber security because every stage in the pipeline can be tampered with. An attacker who changes simulation assets, training inputs, or configuration files may poison a model, hide unsafe behavior, or make a system fail when it leaves the lab. Defenders treat the pipeline as part of the trusted computing base, using signed artifacts, provenance tracking, access control, reproducible builds, and integrity checks to make sure simulation results are reliable and deployment decisions are based on valid test data.