Cybersecurity is critical for national infrastructure, governments at all levels, the military, industry, and individual privacy. Both the government and industrial sectors in the U.S. foresee a substantial need for a proficient cybersecurity workforce. To tackle this challenge, the National Security Agency (NSA) and the National Science Foundation (NSF) jointly sponsored the GenCyber program with the goal of sparking K-12 students’ interest in cybersecurity and enhancing their knowledge of cybersecurity practices and safe online behavior. In support of the GenCyber program, this paper presents the first-of-its-kind autonomous R/C car-based cybersecurity summer camp for high school students, featuring an inclusive curriculum that seamlessly integrates concepts of machine learning (ML)/artificial intelligence (AI) and cybersecurity through the lens of an important ML application—autonomous vehicles. Beginning with an introduction to basic cybersecurity topics and technical concepts, the curriculum enables students to explore ML through hands-on experiences such as collecting front-camera images and training an autonomous driving ML model. Additionally, a series of engaging cybersecurity projects are developed focusing on secure shell (SSH) password cracking, buffer overflow attacks, and man-in-the-middle attacks. These projects are designed to launch various cybersecurity attacks against the students’ self-built autonomous driving models, enhancing the teaching effectiveness and awareness of cybersecurity. Our pre- and post-camp surveys demonstrate that the camp significantly boosted students’ confidence in computing, cybersecurity, and ML/AI.