VP of Engineering

Nightfall has launched an AI Browser Security solution to prevent real-time data exfiltration through AI tools and modern web workflows that traditional data loss prevention systems cannot monitor. The platform addresses security gaps as employees increasingly use ChatGPT, Claude, and other AI tools by pasting code, uploading spreadsheets and sharing screenshots. The solution operates directly within browsers including Chrome, Edge and AI-native browsers, intercepting file uploads, clipboard actions and screenshot sharing before transmission. It combines browser-native interception with endpoint monitoring and SaaS API enforcement, using machine learning and computer vision to detect sensitive information including credentials, source code and proprietary data. The San Francisco-based company is backed by Bain Capital Ventures, Venrock and WestBridge Capital.

Nightfall expands data protection with AI Browser Security for browsers, endpoints and SaaS. Cloud data protection startup Nightfall today announced the launch of its AI Browser Security solution, a new solution designed to stop real-time data theft through artificial intelligence tools, AI-powered browsers and modern web workflows that legacy data loss prevention solutions cannot see or control. The solution seeks to assist with the issue that has arisen 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. Nightfall argues that traditional data loss prevention tools, which were built for email attachments, USB drives and static pattern matching, lack visibility inside browsers and encrypted sessions. As a result, they leave organizations blind to their fastest-growing data loss vector. The new AI Browser Security solution closes the gap through the provision of an AI-native security architecture. It operates directly with the browser and with endpoint and software-as-a-service layers where exfiltration, or theft, occurs in 2026 to deliver real-time prevention before sensitive data ever leaves the organization. According to Nightfall, in 2026, data exfiltration can include proprietary source code being pasted directly into AI chat interfaces, financial and customer data being dragged into AI tools over encrypted HTTPS, screenshots and images that bypass file-based controls entirely and data lineage that is lost as content moves between SaaS apps, endpoints and browsers. Because traditional data loss prevention relies on regular-expression rules, network inspection and after-the-fact alerts, Nightfall says, these workflows often go undetected until sensitive data has already left the organization. "Employees aren't bypassing security out of malice; they're pasting code, uploading spreadsheets and sharing screenshots to get work done," said co-founder and Chief Executive Rohan Sathe. "Legacy data loss prevention 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." Nightfall's AI Browser Security solution delivers coverage across every major data exfiltration path, starting with browser-native interception. The solution works directly inside modern browsers and AI browsers to provide real-time visibility into file uploads, clipboard paste actions, form submissions and screenshot-based sharing to any website or AI application. The content is analyzed and blocked before transmission, without proxies, SSL inspection or workflow disruption. For endpoint protection, the solution offers protection beyond the browser by monitoring cloud sync tools, desktop AI applications, Git and command-line operations, USB transfers, printing and clipboard activity across applications. For SaaS, the solution works with leading cloud platforms to deliver continuous scanning of data at rest and in motion, with full visibility into where sensitive data originates, how it's transformed and where it's headed. Core to the offering is Nightfall's AI-native detection engine, which applies machine learning and large language models to identify sensitive data with high precision and without manual tuning. The engine can detect credentials, personally identifiable information, payment card data and protected health information while also understanding business context. That way it can classify content such as source code, customer lists, financial projections, board materials and proprietary intellectual property. The detection engine comes with computer vision and optical character recognition to identify sensitive information embedded in screenshots, scanned documents and images before they are shared. It also offers unified data lineage capabilities to trace content from its source to its attempted destination. That gives security teams forensic-grade visibility and enables real-time enforcement across browsers, endpoints and SaaS applications. Nightfall applies a single, unified policy framework across all layers of enforcement that allows security teams to define rules without the need to manage disconnected tools or inconsistent controls. The company adds that the unified approach allows organizations to safely enable AI adoption while maintaining the visibility, governance and control required in regulated and high-risk environments. 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