This study investigates the impact of cyberattacks on traffic flow stability, particularly focusing on the passing behavior of connected vehicles (CAVs). The authors extend a car-following model to incorporate passing maneuvers and analyze the effects of cyberattacks using linear and nonlinear stability analyses. The linear stability analysis identifies neutral stability conditions for different parameters, while the nonlinear analysis uses the reductive perturbation method to derive equations (Burgers, KdV, and mKdV) that describe various wave patterns, reflecting stable, metastable, and unstable areas of autonomous vehicle flow. The findings indicate that cyberattacks can worsen traffic flow stability during passing, leading to more chaotic conditions and increased instability. Numerical simulations confirm that the proposed model effectively captures the behavior of connected vehicles under cyberattacks, showing that a low passing rate leads to a phase transition from the no-jam region to the kink-jam region, while an increase in the passing rate results in a transition to a more chaotic traffic pattern. The study highlights the importance of addressing cybersecurity threats to prevent collisions and alleviate traffic congestion.This study investigates the impact of cyberattacks on traffic flow stability, particularly focusing on the passing behavior of connected vehicles (CAVs). The authors extend a car-following model to incorporate passing maneuvers and analyze the effects of cyberattacks using linear and nonlinear stability analyses. The linear stability analysis identifies neutral stability conditions for different parameters, while the nonlinear analysis uses the reductive perturbation method to derive equations (Burgers, KdV, and mKdV) that describe various wave patterns, reflecting stable, metastable, and unstable areas of autonomous vehicle flow. The findings indicate that cyberattacks can worsen traffic flow stability during passing, leading to more chaotic conditions and increased instability. Numerical simulations confirm that the proposed model effectively captures the behavior of connected vehicles under cyberattacks, showing that a low passing rate leads to a phase transition from the no-jam region to the kink-jam region, while an increase in the passing rate results in a transition to a more chaotic traffic pattern. The study highlights the importance of addressing cybersecurity threats to prevent collisions and alleviate traffic congestion.