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Netskope: Managing AI Security Risks in Manufacturing

netskope
06/27/2026
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on everything you put in. So if you're an organization like Renesas that relies on IP and manufacturing technology, anything you put into an AI becomes part of that. And we've seen a number of cases where source code, firmware, even designs have been put into AI for testing, which then public. So an organization that's entire revenue stream relies on its intellectual property, you're giving that intellectual property away. That's one big risk. The second big risk is poisoning. So a lot of AI is being used to generate code, it's being used to help engineers be more productive, but you have to accept the fact that AI is often wrong. The way that Netscope has helped is to give us a great deal of visibility and also actually something called their Cloud Confidence Index. So we rely on that to help shape our policy towards particular AIs. We do a lot of supply chain analysis to ensure that any AI we do business with in terms of a contract is a suitable partner, but the AI Cloud Confidence Index is very effective in just telling us the underlying security risks of an associated platform. Microsoft Mechanics www.microsoft.com

TL;DR

  • AI platforms can inadvertently expose intellectual property when users input sensitive data like source code, firmware, or designs that become part of the AI's training data
  • AI-generated code and outputs carry reliability risks since AI systems are frequently wrong, requiring validation processes for engineering productivity tools
  • Netskope's Cloud Confidence Index helps organizations assess the underlying security risks of AI platforms and shape usage policies accordingly

Summary

This brief interview addresses the critical security challenges organizations face when adopting AI technologies, particularly for companies dependent on intellectual property protection. The speaker, representing Renesas (a semiconductor and manufacturing technology company), outlines two primary AI-related risks: inadvertent IP exposure through AI training data and the reliability concerns of AI-generated code. The discussion highlights how Netskope's Cloud Confidence Index provides visibility into AI platform security posture, enabling organizations to make informed policy decisions about which AI tools are suitable for enterprise use. The approach combines technical controls with vendor due diligence to balance AI productivity gains against security and IP protection requirements.

Chapters

0:00 - AI IP Exposure Risks
0:38 - AI Reliability Concerns
0:52 - Netskope Security Controls

Key Quotes

0:12 "If you're an organization like Renesas that relies on IP and manufacturing technology, anything you put into an AI becomes part of that."
0:52 "We rely on that to help shape our policy towards particular AIs."

FAQ

What is Netskope's Cloud Confidence Index?

The Cloud Confidence Index is a security assessment tool that evaluates the underlying security risks of AI and cloud platforms, helping organizations make informed decisions about which services are suitable for enterprise use based on their security posture.


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