AetherGuard AI: Zero-Trust Firewall for the Generative Era

AetherGuard AI is presented as a holistic AI Trust & Integrity Gateway that expands the typical AI firewall paradigm to offer real-time semantic inspection, cryptographic accountability, responsible AI compliance, and robust operational governance. The system operates as a transparent reverse-proxy between LLM clients and providers, intercepting every prompt and response for multi-dimensional analysis before permitting egress or ingress. This paper makes the following primary contributions: A unified semantic firewall architecture integrating prompt security, responsible AI compliance, data privacy, model integrity, and operational governance in a single pipeline. A systematic threat taxonomy for LLM deployments with concrete mapping to open-source and cloud-native mitigation tools. A production-ready AWS reference implementation with multi-region support, sub-22 ms overhead, and a full DevOps blueprint. Empirical evaluation across security efficacy, latency, compliance, and operational usability dimensions.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-08
DOI
https://doi.org/10.5281/zenodo.18909457
Primary Topic
Network Packet Processing and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

AetherGuard AI: Zero-Trust Firewall for the Generative Era

Muhammad Aamir
Zenodo (CERN European Organization for Nuclear Research)
Network Packet Processing and Optimization
article

AetherGuard AI: Zero-Trust Firewall for the Generative Era

Muhammad Aamir
article en

Abstract

AetherGuard AI is presented as a holistic AI Trust & Integrity Gateway that expands the typical AI firewall paradigm to offer real-time semantic inspection, cryptographic accountability, responsible AI compliance, and robust operational governance. The system operates as a transparent reverse-proxy between LLM clients and providers, intercepting every prompt and response for multi-dimensional analysis before permitting egress or ingress. This paper makes the following primary contributions: A unified semantic firewall architecture integrating prompt security, responsible AI compliance, data privacy, model integrity, and operational governance in a single pipeline. A systematic threat taxonomy for LLM deployments with concrete mapping to open-source and cloud-native mitigation tools. A production-ready AWS reference implementation with multi-region support, sub-22 ms overhead, and a full DevOps blueprint. Empirical evaluation across security efficacy, latency, compliance, and operational usability dimensions.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 51%
Network Packet Processing and Optimization
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