DLP for Copilot & ChatGPT
GitHub Copilot and ChatGPT are the most widely adopted AI tools in the enterprise — and the biggest DLP blind spots. Traditional DLP has zero visibility into what data employees share with these tools. PromptWall provides consistent data protection across both.
The Copilot challenge
GitHub Copilot processes code context automatically — including proprietary source code, API keys, database connection strings, and internal URLs. Unlike ChatGPT where users consciously paste content, Copilot sends context automatically with every keystroke. Developers may not realize that their proprietary codebase is being sent to an external service.
Traditional DLP tools cannot inspect IDE-level AI interactions. They monitor network egress and email attachments — not code editor context windows. PromptWall's editor integration sits inside VS Code and Cursor, inspecting every context block before it reaches the Copilot service.
The ChatGPT challenge
Employees routinely paste customer records, HR data, legal documents, and financial analysis into ChatGPT. These interactions happen through the browser — encrypted HTTPS traffic to an allowed domain. Network-level DLP sees this as normal web traffic and cannot inspect the content.
PromptWall's browser extension intercepts prompts at the DOM level — inside the browser, before the HTTPS request — enabling PII detection and masking that network DLP cannot provide.
Coverage by AI tool
| AI Tool | Surface | Key Risks | PromptWall Coverage |
|---|---|---|---|
| ChatGPT | Browser | Customer PII, internal documents, confidential strategies | Chrome extension intercepts DOM submissions |
| GitHub Copilot | Editor | Proprietary source code, API keys, credentials | VS Code / Cursor extension inspects code context |
| Claude | Browser | HR data, legal documents, financial analysis | Chrome extension with Claude-specific interception |
| Gemini | Browser | Product roadmaps, competitive intelligence | Chrome extension covers Google AI surfaces |
| API Usage | CLI | Batch processing with sensitive data, automated pipelines | Local proxy captures all outbound AI API calls |
Unified policy enforcement
The critical advantage of PromptWall is one policy engine governing all AI surfaces. The same PII detection rules, injection prevention, and policy enforcement apply whether an employee uses ChatGPT in Chrome, Copilot in VS Code, or a Python script calling the OpenAI API.
This eliminates the fragmentation problem where different tools have different security levels. Every AI interaction is inspected, logged, and governed consistently — with complete audit trail visibility.
Why traditional DLP fails here
Traditional DLP was designed for email attachments, USB drives, and file transfers. It operates at the network layer, monitoring egress traffic for known data patterns. AI prompt traffic is fundamentally different:
- Encrypted HTTPS to allowed domains (no network-level content inspection)
- Natural language format (not structured file types DLP expects)
- Browser DOM interactions (invisible to endpoint DLP agents)
- IDE context windows (not file operations DLP monitors)
Secure your AI tools today
Deploy DLP controls across ChatGPT, Copilot, and all AI tools.
Frequently asked questions
Can DLP work with GitHub Copilot?+
Yes. PromptWall's editor integration sits between Copilot and the AI provider, inspecting code context sent for completion. It detects API keys, connection strings, credentials, and proprietary code patterns before they reach the Copilot service.
Does DLP slow down ChatGPT usage?+
PromptWall adds less than 100ms of inspection overhead — imperceptible compared to ChatGPT's 1–10 second response times. The browser extension runs detection in parallel to provide a seamless user experience.
Can I allow ChatGPT but block sensitive data?+
Yes. This is the recommended approach. PromptWall's policy engine supports nuanced controls: allow AI tool usage, but mask PII, block credential patterns, and flag proprietary code. Users remain productive while sensitive data is protected.
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