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Enterprise AI deployments need governance and segmentation after red-team failures

Defensive Guidance
First reported
Last updated
Happening score
H score 10
2 unique sources, 2 articles

Summary

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Enterprise AI deployments are exposing familiar security gaps, making governance, segmentation, and red-team validation urgent to reduce the risk of data theft, policy bypass, and control failures. Basic hygiene mistakes such as unencrypted communication streams and weak classification controls can let AI workflows undermine DLP protections.

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Timeline

  1. 24.04.2026 15:10 2 articles · 1mo ago

    Mandiant warns enterprise AI deployments need governance and segmentation

    Mitigation Patch Update

    Jurgen Kutscher of Mandiant, speaking during Google Cloud Next 26, warned that enterprise AI adoption is reviving basic security failures and that AI workflows are often deployed without basic controls. He said Mandiant red-team engagements found attackers able to change data classifications and bypass DLP protections, observed an unencrypted communication stream between the AI and the browser at a financial company, and used social engineering plus AI-driven follow-on actions to carry out exfiltration and policy changes; he urged organizations to build AI security governance, revisit secure architecture, and validate segmentation with red teaming.

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