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	<title>data security &#8211; BIOENGINEER.ORG</title>
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		<title>Hidden in Plain Prompt: How a Subtle Design Flaw Leaks Database Secrets to AI Models</title>
		<link>https://bioengineer.org/hidden-in-plain-prompt-how-a-subtle-design-flaw-leaks-database-secrets-to-ai-models/</link>
		
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		<pubDate>Wed, 07 Oct 2026 07:36:14 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[AI compliance]]></category>
		<category><![CDATA[BIRD benchmark]]></category>
		<category><![CDATA[credit rating agencies]]></category>
		<category><![CDATA[data security]]></category>
		<category><![CDATA[information hiding]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[model-dependent accuracy]]></category>
		<category><![CDATA[prompt architecture]]></category>
		<category><![CDATA[schema identifier exposure]]></category>
		<category><![CDATA[selective encapsulation]]></category>
		<category><![CDATA[semantic layer]]></category>
		<category><![CDATA[Text-to-SQL]]></category>
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					<description><![CDATA[A new study finds that a Semantic Layer designed to hide sensitive database schema from external AI models silently fails unless the concept-to-SQL mapping is withheld from the prompt, with accuracy benefits that depend heavily on both the model and the workload.]]></description>
		
		
		
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