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Español(ES) adi-shield v0.1.0: detección de inyección de prompt en 5 vectores

Open-source tools combat LLM prompt injection attacks

By PulseAugur Editorial · [2 sources] ·

Two open-source projects have been released to combat prompt injection attacks against large language models. The first, developed by BordairAPI, features a two-stage detection system combining a fast regex gate with a quantized DeBERTa-v3 model, and includes real-world attack data from a game. The second project, adi-shield, focuses on marking untrusted data sources and detecting injected instructions before an agent executes them, without relying on the LLM itself. AI

IMPACT Provides developers with open-source tools to enhance the security of LLM applications against prompt injection.

RANK_REASON Open-source release of tools for detecting prompt injection attacks.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Open-source tools combat LLM prompt injection attacks

COVERAGE [2]

  1. r/MachineLearning TIER_1 English(EN) · /u/BordairAPI ·

    Open-sourcing a two-stage prompt-injection detector (regex gate + quantised DeBERTa-v3 ONNX), trained partly on real attacks from a game I ran [P]

    <!-- SC_OFF --><div class="md"><p>I built a prompt-injection detector for LLM inputs and I've open-sourced the whole thing - code, weights, and the dataset.</p> <p>The design is two stages. A regex layer (around 430 patterns, plus a decode-then-scan step for base64/ROT13/leetspea…

  2. dev.to — LLM tag TIER_1 Español(ES) · Fenix ·

    adi-shield v0.1.0: prompt injection detection in 5 vectors

    <h1> adi-shield v0.1.0: detección de inyección de prompt en 5 vectores </h1> <blockquote> <p>Sensor de defensa que marca datos no confiables y detecta instrucciones<br /> inyectadas antes de que el agente las ejecute, sin depender del modelo.</p> </blockquote> <h2> El problema </…

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