The development of VANETs brings hope for intelligent transportation. However, due to the dynamic and random feature of vehicles, the topology of the VANETs is constantly changing, making it vulnerable to hacker attacks that can lead to vehicle congestion, car accidents and even more serious consequences. The most notorious attacks are Black-Hole Attacks (BHA) and Gray-Hole Attacks (GHA). There are usually four variants of them: routing BHA, Intelligent BHA, Node-Dependent GHA, and Time-Dependent GHA. For these four types of attacks, this paper proposes a lightweight detection scheme that divides the detection process into three stages, using the proposed RR threshold algorithm, intersection algorithm, and forwarding rate-based algorithm to effectively detect malicious vehicles through the cooperation of Vehicles and Road Side Units (RSUs). This approach offloads computational tasks to the network’s upper layers, thereby reducing the computational load on vehicles. Performance analysis results demonstrate that the algorithm is highly efficient and broadly applicable.