Surveillance Detection Scout is a hardware and software stack that makes use of your Tesla’s cameras to tell you if you’re being followed in real-time. The name, as you likely gathered, pays homage to the ever-effective “Surveillance Detection Route”. When parked, Scout makes an excellent static surveillance practitioner as well, allowing you to run queries and establish patterns-of-life on detected persons.
Scout currently supports Tesla Models S, 3 and X, running license plate recognition on 3 camera feeds to alert you in real time if you’re being followed. When you park, Scout remains vigilant, implementing familiar face detection as well. By combining timestamped vehicle location data & video, computer vision and an intuitive web interface, it becomes apparent that Scout has just as many offensive as defensive applications. Over time, SDS captures and reports on observed patterns of life, allowing you to quickly gain an overview of your surroundings (or your target) with minimal effort.
Scout v0.1 has been released, and we’re hard at work on the next iteration. There’s plenty of work to do, but we’re proud to be on the cutting edge of what we feel is an extremely important part of offensive security- leveraging the mass data that’s already out there and opening the public’s eyes to the dangers they face in this day & age.
Dragnet is built on a Vue.js front end, making use of a MongoDB backend, Node.js & Express for the endpoint, and a mix of Keras, Tensorflow, Darknet/YoloV3 and Nvidia TensorRT for computer vision.
Get Scout on Github.