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Tenable broadens AI visibility across major LLMs and AI tools

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Tenable broadens AI visibility across major LLMs and AI tools

Tenable expanded its AI security capabilities within its Tenable One platform to provide visibility across major large language models including Google Gemini, Anthropic Claude, OpenAI ChatGPT Enterprise, and Microsoft Copilot. The update also extends discovery to Model Context Protocol (MCP) deployments and AI-native integrated development environment (IDE) tools, giving security teams broader coverage of AI tool usage in their environments.

Why it matters: Security practitioners managing AI adoption need visibility into which generative AI tools and models developers are using to prevent data exposure and unauthorized integration risks.

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Tenable broadens AI visibility across major LLMs and AI tools

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ai security

Tenable broadens AI visibility across major LLMs and AI tools

Tenable expanded its exposure management platform to detect artificial intelligence (AI) security risks across additional large language models, including Google Gemini, Anthropic Claude, OpenAI ChatGPT Enterprise, and Microsoft Copilot. The update also covers Model Context Protocol deployments and AI-native integrated development environment tools, broadening visibility into an organization's AI infrastructure footprint.

Why it matters: Security teams gain better inventory and control over shadow AI adoption in the enterprise, reducing the risk of unmanaged generative AI exposures that could leak sensitive data or introduce compliance gaps.

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Correction

Correction recorded as of .

ai security

Tenable broadens AI visibility across major LLMs and AI tools

Tenable expanded its exposure management platform to detect artificial intelligence (AI) security risks across additional large language models, including Google Gemini, Anthropic Claude, OpenAI ChatGPT Enterprise, and Microsoft Copilot. The update also covers Model Context Protocol deployments and AI-native integrated development environment tools, broadening visibility into an organization's AI infrastructure footprint.

Why it matters: Security teams gain better inventory and control over shadow AI adoption in the enterprise, reducing the risk of unmanaged generative AI exposures that could leak sensitive data or introduce compliance gaps.

VendorsMicrosoftGoogle
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