{"id":236832,"date":"2026-06-25T03:35:07","date_gmt":"2026-06-25T07:35:07","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/06\/25\/forget-data-leakage-shadow-ais-real-threat-is-access-control\/"},"modified":"2026-06-25T03:35:09","modified_gmt":"2026-06-25T07:35:09","slug":"forget-data-leakage-shadow-ais-real-threat-is-access-control","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/06\/25\/forget-data-leakage-shadow-ais-real-threat-is-access-control\/","title":{"rendered":"Forget Data Leakage: Shadow AI’s Real Threat Is Access Control"},"content":{"rendered":"

Forget Data Leakage: Shadow AI’s Real Threat Is Access Control<\/a><\/p>\n

https:\/\/thehackernews.com\/2026\/06\/forget-data-leakage-shadow-ais-real.html<\/a><\/p>\n

Publish Date: 2026-06-19 06:30:00<\/a><\/p>\n

Source Domain: thehackernews.com<\/a><\/p>\n

Summary:<\/strong>
\nThe evolving landscape of enterprise AI has transformed from a simple concern of data leakage to an intricate issue of access control. Initially, enterprise security teams focused on preventing sensitive data from being unintentionally input into public AI tools through policies and usage restrictions. However, this traditional approach is inadequate in the current scenario where employees rapidly develop internal AI agents for tasks such as coding, workflow automation, and various business processes through diverse platforms and tools. These agents pose a higher risk due to their ability to interact with enterprise systems, perform substantial changes, and retain permissions long after their inception. Unlike shadow IT, which merely serves as data endpoints, agentic AI can autonomously execute actions that pose significant access control threats. Existing security controls, designed for human users and conventional workloads, are ineffective against AI agents’ unpredictable behavior and complex interactions with multiple enterprise systems. The challenge now is to systematically discover, manage, and enforce controls over these AI agents through continuous inventory, ownership tracking, understanding resource connections, managing access credentials, monitoring activity, and ensuring dormant agents are decommissioned. The goal is not to stifle AI adoption but to enable it under secure governance, ensuring a balanced approach wherein organizations harness productivity gains without compromising security.<\/p>\n

Key Points:<\/strong><\/p>\n