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Open-source proxy Jnvoy shields LLM calls from PII and prompt injection

By PulseAugur Editorial · [1 sources] ·

Developer Jnvoy has created an open-source proxy tool called Jnvoy that aims to protect sensitive user data and prevent prompt injection attacks before requests reach large language models like Claude and GPT-4o. The proxy scans and redacts Personally Identifiable Information (PII) locally, replacing it with reversible tokens, and also detects and blocks various forms of prompt injection and tool poisoning. Jnvoy is designed for easy integration, requiring only a single URL change in application code, and offers features such as compliance reporting for regulations like GDPR and the EU AI Act, semantic caching for cost savings, and audit logs. AI

IMPACT Enhances LLM application security by preventing sensitive data leakage and prompt injection attacks.

RANK_REASON The item describes a new open-source tool for enhancing AI safety and data privacy.

Read on dev.to — LLM tag →

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

Open-source proxy Jnvoy shields LLM calls from PII and prompt injection

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Signal score
30 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
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Tool
The item describes a new open-source tool for enhancing AI safety and data privacy.
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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, safety
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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) · JEEVAN NAGARAJ ·

    I built an open source proxy that blocks PII and prompt injection before any LLM call

    <h2> The problem </h2> <p>Every time your application calls Claude or GPT-4o, your users' sensitive data travels to an external server. Names, emails, phone numbers, NHS numbers, financial data. Most developers have no visibility into what is actually leaving their system.</p> <h…

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