Identifiers & Contact Info
Sensitive Numbers
of AI data breaches involve exposed emails or SSNs
— Cybersecurity AI Report 2024
When preparing data for AI, specific PII entities like emails, phone numbers, and SSNs represent the highest immediate risk. Removing emails from text is the most common prerequisite before pasting data into commercial AI models.
Treating each PII entity type with zero-trust local tokenization is essential. This is exactly how to mask data for ChatGPT effectively.
Why Zero-Trust Beats Every Alternative
How PrivacyScrubber compares to common approaches in Entity workflows.
| Approach | PII sent to AI? | Reversible? | Compliance-safe? |
|---|---|---|---|
| Passing raw emails to AI | ✅ yes | ❌ no | ❌ no |
| Manual find-and-replace | partial | ❌ no | partial |
| PrivacyScrubber Entity Tagger | ❌ never | ✅ yes | ✅ yes |
Try PrivacyScrubber Free
No account. No install. Works fully offline. Your Entity data never leaves your browser.
How to Use AI Safely in 3 Steps
The zero-trust workflow for this field — verified by airplane mode test.
Identify specific PII entities
Determine which data types (SSNs, emails, phones) are present in your text and must be guarded from AI ingestion.
Sanitize entities locally
Paste your text into PrivacyScrubber. Entities are isolated and replaced with secure tokens right in your browser.
Process safely and restore
Use the AI on the tokenized text, then reinsert original entities locally without exposing them.
Frequently Asked Questions
Common questions about AI data privacy in this field, answered.
Why is it important to remove emails before AI processing?
Emails directly link sensitive prompt context to actual individuals. Preventing their exposure stops the AI from mapping generated data or private queries to a specific person.
Can AI models memorize SSNs?
Yes. LLMs have been shown to memorize exact sequences like SSNs and credit card numbers from training data. Scrubbing this data locally prevents it from entering the model.
What happens if I forget to scrub a phone number?
The phone number is typically logged by the AI provider and could be subjected to human review or used in fine-tuning, posing a privacy risk.
Does the local scrubber support custom entities?
Yes. The PRO version supports defining custom regex patterns to catch domain-specific identifiers or proprietary part numbers before AI ingestion.
Key Terms in Entity AI Privacy
Definitions that matter for understanding PII risk in entity workflows.
- Entity Extraction
- The process of identifying specific types of data (like names or SSNs) within unstructured text.
- SSN Scrubbing
- Using strict regex patterns to eliminate Social Security Numbers, one of the most high-risk PII elements.
- Contact Masking
- Replacing emails and phone numbers with placeholders, ensuring communication details stay private.