<p>This paper introduces a single-source framework that ensures robust and intelligent 6G wireless network management through combined deep anomaly detection and threat validation by blockchain. Generalized Simplicial Quantum Equivariant Convolutional Attention Network (GSQE-CAtN-PoFO) is proposed as a unified deep-learning approach to learn quantum-equivariant spatial patterns and higher-order topological interactions to accurately identify anomalies. Class center imputation of missing values is a mechanism to improve data completeness and strength, and log storage and query blockchain to generate tamper-proof threat logging data and to provide efficient retrieval. The experimental findings indicate that the proposed GSQE-CAtN-PoFO has a high detection, short response, and throughput in comparison to the current methods, making it an effective and scalable solution to 6G network security management.</p>