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SentinelOne enhances AI security with data security posture management

SentinelOne expands its AI Security Platform with new DSPM features to help secure AI systems amid increasing regulatory requirements.

  • Wednesday, 18th February 2026 Posted 3 months ago in by Sophie Milburn
SentinelOne, the AI-native security firm, has expanded its AI Security Platform with new Data Security Posture Management (DSPM) capabilities. These are designed to protect artificial intelligence (AI) systems from initial data ingestion through to runtime execution. The enhancements enable organisations to advance their AI initiatives while maintaining compliance with privacy and regulatory standards, reducing the risk of data breaches, and supporting AI-driven innovation and automation.

As AI adoption moves from experimental phases to widespread production, new risks arise that can affect business speed, trust, and regulatory compliance. AI’s integration across data systems, cloud services, and production workflows increases potential attack surfaces, requiring a comprehensive approach that safeguards data, infrastructure, and runtime collectively.

SentinelOne’s DSPM features serve as the initial layer of AI security, helping organisations prevent sensitive or high-risk data from entering AI pipelines. This addresses risks such as data memorisation and pipeline contamination before training begins.

These capabilities complement SentinelOne’s existing measures, including cloud infrastructure posture management (CSPM), AI Security Posture Management (AI-SPM), runtime workload protection, employee GenAI security, and agent security, creating a more complete AI Security Platform.

The integrated approach allows security teams to monitor risks across the AI lifecycle, limit lateral movement from data to core AI logic, and maintain protection of AI systems in operational environments.

“As AI systems become more powerful and more autonomous, security must evolve to match that reality,” said Gregor Stewart, Chief AI Officer at SentinelOne. “AI security is not a point problem. It is a lifecycle problem. Data security is the first mile, but true protection requires securing everything AI is built on, from data and infrastructure to runtime behavior.”

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