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Network-based Data Loss Prevention for Generative AI Platforms

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📰 1 unique sources, 1 articles

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Organizations are increasingly adopting generative AI platforms like ChatGPT, Gemini, Copilot, and Claude, which improve efficiency but also introduce new data leak risks. Sensitive information can be shared through chat prompts, file uploads, or browser plugins, often bypassing traditional data loss prevention (DLP) tools. Network-based DLP solutions, such as Fidelis Network® Detection and Response (NDR), offer a way to monitor, enforce policies, and audit GenAI usage across the entire network traffic path. This approach helps in identifying threats as they traverse the network, even if the content is encrypted. Organizations can use GenAI DLP solutions through three complementary approaches: URL-based indicators with real-time alerts, metadata-only monitoring for audit and low-noise environments, and detecting risky file uploads. Each method has its advantages and considerations, allowing organizations to tailor their monitoring strategies based on risk and business needs. Comprehensive AI data protection involves maintaining live lists of GenAI endpoints, assigning appropriate monitoring modes, integrating with existing SOC workflows, and educating users on policy compliance.

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  1. 29.08.2025 13:30 📰 1 articles

    Network-based DLP solutions introduced for monitoring generative AI platforms

    Network-based data loss prevention solutions, such as Fidelis Network® Detection and Response (NDR), have been introduced to monitor, enforce policies, and audit generative AI (GenAI) usage across the entire network traffic path. This approach helps in identifying threats as they traverse the network, even if the content is encrypted. Organizations can use GenAI DLP solutions through three complementary approaches: URL-based indicators with real-time alerts, metadata-only monitoring for audit and low-noise environments, and detecting risky file uploads. Each method has its advantages and considerations, allowing organizations to tailor their monitoring strategies based on risk and business needs.

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