targeting security and privacy professionals debating DLP strategy.
The Challenge
Post-hoc anonymization — cleaning data after it's already been shared with external systems — is insufficient for AI data privacy protection. When an employee types a customer name into ChatGPT, the data leaves the organization's control in real-time. Log monitoring, DLP tools, and after-the-fact anonymization cannot un-ring this bell. The Samsung ChatGPT incident (March 2023) demonstrated this: source code was shared with ChatGPT before any monitoring or prevention system could intervene. Organizations need prevention at the point of entry, not detection after the fact. The 2025 Cyberhaven study found 11% of all ChatGPT prompts contain confidential or personal data.
By the Numbers
- The Samsung ChatGPT incident (March 2023) demonstrated this: source code was shared with ChatGPT before any monitoring or prevention system could intervene.
- The 2025 Cyberhaven study found 11% of all ChatGPT prompts contain confidential or personal data.
Real-World Scenario
A law firm's associates use Claude to draft contract summaries. The Chrome Extension highlights client names, case numbers, and financial figures in the Claude input field before submission. Associates can anonymize with one click before sending. In 6 months of deployment, zero client PII incidents vs. 3 incidents in the previous 6 months (before extension deployment). The managing partner credits the real-time prevention model for the improvement.
Technical Approach
The Chrome Extension provides real-time PII detection with inline highlighting directly in the ChatGPT, Claude, and Gemini input fields. Detection happens client-side before data is submitted. Highlighted PII can be anonymized with one click before submission. The user sees which entities were detected and their confidence scores, enabling informed decisions about what to share. Prevention at the point of entry, not detection after the fact.
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