We propose a novel method (FaCE) for normal estimation of unoriented point clouds and VR ribbon sketches that leverages a modeling of the Faraday cage effect. Our method is uniquely robust to the presence of interior structures and artifacts, producing superior surfacing output when combined with Poisson Surface Reconstruction. Left: A VR ribbon sketch [Rosales et al. 2021, 2019] is sparsified to mimic a simpler, plausible user input, and points are evenly sampled from the ribbons. Middle: Points form a Faraday cage around the interior. Electric potentials under various linear external fields, and the maximum electric field strength over these scenarios are shown. Right: Gradient information from maximum field strength is used to estimate normals and filter interior parts of ribbons. Poisson Surface Reconstruction [Kazhdan and Hoppe 2013] is used to generate the surface free of interior structures and concavities at intersecting points.