Nightfall announced the launch of its AI Browser Security solution, designed to stop real-time data exfiltration through AI tools, AI-powered browsers, and modern web workflows that legacy data loss prevention (DLP) solutions cannot see or control.
As employees increasingly rely on ChatGPT, Claude, Gemini, Copilot, and emerging AI-native browsers to analyze documents, debug code, and summarize business data, sensitive information is routinely exposed through browser-based uploads, clipboard pastes, screenshots, and autonomous agent interactions. Traditional DLP tools-built for email attachments, USB drives, and static pattern matching-lack visibility inside browsers and encrypted sessions, leaving organizations blind to their fastest-growing data loss vector.
Nightfall closes this gap with an AI-native security architecture that operates directly at the browser, endpoint, and SaaS layers-where modern exfiltration actually happens-enabling real-time prevention before sensitive data ever leaves the organization.
“AI browsers are fast becoming the primary data exfiltration channel inside the enterprise,” said Rohan Sathe, CEO and co-founder of Nightfall. “Employees aren’t bypassing security out of malice; they’re pasting code, uploading spreadsheets, and sharing screenshots to get work done. Legacy DLP was never designed to see or understand those actions. Nightfall‘s AI-native browser security gives teams visibility and control at the exact moment data is shared.”
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Shadow AI Has Outpaced Legacy Security
Legacy security architectures were designed for a pre-AI world, where sensitive data moved through email, file transfers, and known SaaS applications. Today’s workflows look very different:
- Proprietary source code is pasted directly into AI chat interfaces
- Financial and customer data is dragged into AI tools over encrypted HTTPS
- Screenshots and images bypass file-based controls entirely
- Data lineage is lost as content moves between SaaS apps, endpoints, and browsers
Because traditional DLP relies on regex rules, network inspection, and after-the-fact alerts, these workflows often go undetected—until sensitive data has already left the organization.
SOURCE: PRNewswire