Quickly scanning an environment to determine relative threat or safety is an essential part of survival. Low-level visual features extracted rapidly from the environment may help people detect threats. We probed this link in three experiments. We first extracted curvature, length, and orientation statistics of all images in the International Affective Picture System image set and related them to emotional valence scores. Images containing angular contours were rated as negative, and images containing long contours as positive. We then composed new, content-free line drawings with specific combinations of length, curvature, and orientation values and asked 67 participants to rate them as positive or negative and 97 participants to rate them as safe or threatening. Low curvature, long, horizontal contours were rated as positive/safe, while short, high curvature contours were rated as negative/threatening. Our work shows that low-level scene features help people make judgments about potential threat in the environment.