Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866911654527107072 |
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| author | Arceo, Francisco Javier Narsing, Varsha Prasad |
| author_facet | Arceo, Francisco Javier Narsing, Varsha Prasad |
| contents | Retrieval-Augmented Generation (RAG) and agentic AI systems are increasingly prevalent in enterprise AI deployments. However, real enterprise environments introduce challenges largely absent from academic treatments and consumer-facing APIs: multiple tenants with heterogeneous data, strict access-control requirements, regulatory compliance, and cost pressures that demand shared infrastructure.
A fundamental problem underlies existing RAG architectures in these settings: retrieval systems rank documents by relevance--whether through semantic similarity, keyword matching, or hybrid approaches--not by authorization, so a query from one tenant can surface another tenant's confidential data simply because it scores highest. We formalize this gap and analyze additional shortcomings--including tool-mediated disclosure, context accumulation across turns, and client-side orchestration bypass--that arise when agentic systems conflate relevance with authorization. To address these challenges, we introduce a layered isolation architecture combining policy-aware ingestion, retrieval-time gating, and shared inference, enforced through server-side agentic orchestration. This approach centralizes security-critical operations--tool execution authorization, state isolation, and policy enforcement--on the server, creating natural enforcement points for multitenant isolation while allowing client-side frameworks to retain control over agent composition and latency-sensitive operations.
We validate the proposed architecture through an open-source implementation in OGX, a vendor-neutral framework that implements an OpenAI-compatible, open-source Responses API with server-side multi-turn orchestration. We evaluate it empirically and show that ABAC gating eliminates cross-tenant leakage while introducing negligible overhead. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_05287 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use Arceo, Francisco Javier Narsing, Varsha Prasad Cryptography and Security Artificial Intelligence Information Retrieval Software Engineering I.2; H.3; K.6 Retrieval-Augmented Generation (RAG) and agentic AI systems are increasingly prevalent in enterprise AI deployments. However, real enterprise environments introduce challenges largely absent from academic treatments and consumer-facing APIs: multiple tenants with heterogeneous data, strict access-control requirements, regulatory compliance, and cost pressures that demand shared infrastructure. A fundamental problem underlies existing RAG architectures in these settings: retrieval systems rank documents by relevance--whether through semantic similarity, keyword matching, or hybrid approaches--not by authorization, so a query from one tenant can surface another tenant's confidential data simply because it scores highest. We formalize this gap and analyze additional shortcomings--including tool-mediated disclosure, context accumulation across turns, and client-side orchestration bypass--that arise when agentic systems conflate relevance with authorization. To address these challenges, we introduce a layered isolation architecture combining policy-aware ingestion, retrieval-time gating, and shared inference, enforced through server-side agentic orchestration. This approach centralizes security-critical operations--tool execution authorization, state isolation, and policy enforcement--on the server, creating natural enforcement points for multitenant isolation while allowing client-side frameworks to retain control over agent composition and latency-sensitive operations. We validate the proposed architecture through an open-source implementation in OGX, a vendor-neutral framework that implements an OpenAI-compatible, open-source Responses API with server-side multi-turn orchestration. We evaluate it empirically and show that ABAC gating eliminates cross-tenant leakage while introducing negligible overhead. |
| title | Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use |
| topic | Cryptography and Security Artificial Intelligence Information Retrieval Software Engineering I.2; H.3; K.6 |
| url | https://arxiv.org/abs/2605.05287 |