ZeroTrust-Vault: An Asynchronous Event-Streaming and Cryptographic Audit Ledger for Ransomware Resiliency in Municipal Data Systems

Municipal governments, county courthouses, and local public records registries are transitioning legacy on-premise transactional databases to distributed cloud environments. During this modernization process, systems face acute synchronization and security challenges: wide-area network (WAN) instability frequently causes partial commit failures in standard application-level dual-writes, leading to silent state divergence between on-premise records and cloud replicas. Concurrently, ransomware threat actors exploit the mutable nature of relational database storage, dwelling within systems to alter historical rows or encrypt records prior to detection. Conventional backup methodologies (such as scheduled database snapshots) introduce an unacceptable Recovery Point Objective (RPO) of up to 24 hours and Recovery Time Objectives (RTO) measured in days. This paper presents ZeroTrust-Vault, a lightweight, non-intrusive middleware framework designed to guarantee zero data loss and tamper detection for critical municipal record platforms. ZeroTrust-Vault captures database mutations directly from the database Write-Ahead Log (WAL) at the disk level via log-based Change Data Capture (CDC), decoupling primary transactional execution from cloud replication. Captured mutations are deterministically partitioned into Apache Kafka brokers enforcing transactional Exactly-Once Semantics (EOS). An append-only cryptographic ledger computes sequential SHA-256 hash chains across state transitions, and verified batches are committed to hardware-enforced Write-Once-Read-Many (WORM) storage via AWS S3 Object Lock in Compliance Mode. To detect ongoing ransomware attacks before bulk corruption spreads, the framework instruments real-time payload inspection using Shannon's Information Entropy (H(X)) exposed through the open Model Context Protocol (MCP), triggering automated connection isolation in under 15 milliseconds. In experimental evaluations, the framework achieved an ingestion throughput of 588,171 writes/sec, a p99 latency of 0.012 ms, tamper detection across 5,000 blocks in 2.688 ms, and deterministic state reconstruction yielding a Recovery Point Objective of zero records lost (RPO = 0) with a cloud Recovery Time Objective under 15 minutes (RTO < 15 min).