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New tool gatewayproof finds hidden LLM gateway bugs

A new open-source tool called gatewayproof has been developed to identify and test for five critical bugs in LLM gateways. These bugs, which can masquerade as successful operations, include dropped or reordered stream chunks, inaccurate token usage counts, incorrect cost calculations, cross-stream data leakage, and swallowed upstream errors. The tool works by replacing the actual LLM with a deterministic mock that provides ground truth for responses, token usage, and error conditions, allowing developers to precisely test their gateway's behavior. AI

IMPACT Helps developers ensure the reliability and security of LLM gateway integrations.

RANK_REASON New open-source tool released for testing LLM gateways.

Read on dev.to — LLM tag →

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

New tool gatewayproof finds hidden LLM gateway bugs

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51 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
New open-source tool released for testing LLM gateways.
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Single-source cluster
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
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · ArkNet Digital ·

    Five LLM gateway bugs that look like success (and how to test for them)

    <p>If your app talks to models through an OpenAI-compatible gateway (LiteLLM or one of its many peers), that gateway is doing a lot on every request. It re-streams the response chunk by chunk, recomputes token usage, works out what the request cost, and has to pass upstream failu…