Can Your Security Stack See ChatGPT? Why Network Visibility Matters

Generative AI platforms such as ChatGPT, Gemini, Copilot and Claude are increasingly adopted in organisations, but their use can create new data loss risks as prompts, uploaded files and browser plugins bypass traditional security controls. The piece argues that network-based data loss prevention is needed to monitor GenAI traffic across the entire path, not just endpoints or silos, and highlights Fidelis Network Detection and Response (NDR) as a solution to bring AI activity under policy enforcement and auditing.

It outlines three complementary monitoring approaches: URL-based indicators with real-time alerts for GenAI activity, metadata-only monitoring that preserves session details for audits while minimising noise, and file-upload monitoring that inspects uploads for sensitive information and captures full session context when rules match.

The article notes that alerts can trigger full packet captures and automated actions such as traffic redirects or isolation of suspicious messages, while metadata monitoring supports long-term trend analysis and compliance reporting. It also emphasises the need to keep monitoring rules up to date as AI endpoints and plugins evolve, and discusses the balance between immediate threat detection and low-noise auditing.

According to Fidelis NDR, a combined approach using alert-based, metadata, and file-upload controls helps organisations deploy GenAI safely while preserving both productivity and governance.