Akamai researchers developed a hybrid CNN-BiLSTM-Attention deep learning framework for real-time detection of Domain Generation Algorithms (DGAs) used by modern malware for resilient C2 communications. The approach specifically targets dictionary-based DGAs that generate human-readable domains mimicking legitimate traffic, which traditional static defenses and entropy-based detection methods fail to identify. The framework incorporates adaptive retraining strategies to counter concept drift as DGA techniques evolve.