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	<title>Ajish Abraham &#8211; Noise</title>
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		<title>Preventing data exfiltration in machine learning environments with Amazon SageMaker AI</title>
		<link>https://noise.getoto.net/2026/06/29/preventing-data-exfiltration-in-machine-learning-environments-with-amazon-sagemaker-ai/</link>
		
		<dc:creator><![CDATA[Ajish Abraham]]></dc:creator>
		<pubDate>Mon, 29 Jun 2026 17:16:48 +0000</pubDate>
				<category><![CDATA[Amazon SageMaker AI]]></category>
		<category><![CDATA[Amazon SageMaker Studio]]></category>
		<category><![CDATA[Amazon WorkSpaces Secure Browser]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[In this post, we demonstrate how iBusiness implemented a three-layered security architecture using Amazon SageMaker AI, virtual private cloud (VPC) endpoints, and Amazon WorkSpaces Secure Browser to prevent data exfiltration while maintaining data scientist productivity. You can adapt this approach to build secure machine learning environments that balance strict data protection with team scalability.]]></description>
		
		
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