In the trend of the Internet of Things, 5G technology is one of the important platforms connecting mobile devices to the Internet network. Along with the popularity of 5G network deployment in many countries, the risk of destructive attacks on this infrastructure is increasing. This paper proposes a novel platform for detecting attacks on the AMF in 5G cores using distributed ML. Core innovation: The Attack‐Aware Weighted Aggregation (AAWA) in federated learning enables knowledge sharing without raw data exchange, achieving 99.24% global accuracy (0.77% over FedAvg), 25.6% faster convergence (32 vs. 43 rounds), and robust privacy with differential privacy (ε = 1.0, 0.33% accuracy drop). Experiments on a custom AMF dataset validate superior performance in detection, efficiency, and resilience.