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Open-source engine prevents document leaks in multi-tenant RAG systems

By PulseAugur Editorial · [1 sources] ·

A developer has created an open-source service called Enterprise RAG Engine to address a critical security flaw in multi-tenant retrieval-augmented generation (RAG) systems. The engine ensures that one customer's documents do not leak into another's answers by tagging documents with tenant IDs during ingestion and filtering searches based on these IDs. This approach prevents cross-tenant data exposure, as demonstrated by a test where one company's pricing data was correctly kept separate from another's leave policy query. The developer also identified and fixed a bug in their own isolation logic where a missing tenant ID would inadvertently search all documents. AI

IMPACT Enhances data security and isolation for RAG applications, enabling safer multi-tenant deployments.

RANK_REASON The item describes a newly developed open-source service for a specific technical problem.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Open-source engine prevents document leaks in multi-tenant RAG systems

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44 / 100
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Tool
The item describes a newly developed open-source service for a specific technical problem.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · ALI KHUSROO BIN SABIR ·

    Multi-tenant RAG: stop one customer's documents leaking into another's answers

    <p>Retrieval-augmented generation (RAG) is the standard way to let people "chat with their documents": split the documents into chunks, embed them, store them in a vector database, and at question time retrieve the closest chunks and hand them to an LLM as context.</p> <p>Nearly …

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