This article critiques traditional policy-based data loss prevention (DLP) methods, arguing they can't adapt to the complexity of modern data. It introduces ORION, a solution that uses AI agents to provide context-aware detection of data exfiltration incidents, improving accuracy and reducing false positives. ORION learns organizational data patterns and integrates various data sources for comprehensive protection.

The article discusses the concept of "context-only attack surface," emphasizing how vulnerabilities can exist even when no direct interaction is made with a system. It highlights the importance of understanding the broader context in which systems operate to better identify and mitigate potential security risks.