Is it safe to share {X} with {Y}?

No. Biometric data, including fingerprints, facial geometry, voiceprints, and iris scans, should not be shared with ChatGPT under any normal circumstances. Inputs submitted to ChatGPT may be retained by OpenAI for up to 30 days and used for safety monitoring, meaning biometric identifiers could be stored on external servers outside your control.

Why this matters

  • Biometric data is permanent by nature, unlike passwords it cannot be changed if compromised or exposed through a data breach.
  • OpenAI's default data handling allows human reviewers to access conversation content, which creates a direct exposure risk for any biometric identifiers submitted as text or structured data.
  • Most biometric data is classified as a special category of sensitive data under laws like GDPR and CCPA, meaning its unauthorized processing carries significant legal consequences for the disclosing party.

For enterprise

Employees who input biometric identifiers into ChatGPT outside of approved internal systems create an immediate compliance breach, particularly under regulations that require explicit consent and controlled processing environments for this category of data. Organizations subject to GDPR, BIPA, or similar frameworks face direct regulatory exposure when biometric data leaves sanctioned systems and enters third-party AI platforms without a formal data processing agreement in place.

Compliances at risk

What counts as Biometric Data?

  • Passport numbers
  • Government-issued identification numbers
  • National identity numbers
  • Driver's license numbers
  • Tax identification numbers

Why people share Biometric Data with ChatGPT

  • To draft messages using real names or personal details
  • To understand user data quickly
  • To summarize profiles or records
  • To prepare reports based on user information

What actually happens when you paste Biometric Data into ChatGPT

When you paste Biometric Data into ChatGPT, that data is transmitted from your device to external servers operated by the AI provider.

Depending on system configuration and policies, the data may be logged, temporarily stored, or reviewed for safety and quality purposes. Retention can last from days to weeks, and in some cases may extend beyond the immediate session.

Statements such as “we do not train on your data” do not eliminate risks related to retention, logging, or internal access. These controls vary by product and setting, and are not always visible to end users.

From a governance perspective, any non-zero retention window introduces exposure risk when sensitive data is shared without controls, auditability, or enforcement.

Risks of sharing Biometric Data with ChatGPT

  • Identity theft: Exposed personal details can be used to impersonate individuals across services.
  • Phishing attacks: Leaked contact information enables targeted phishing campaigns.
  • Account takeover: Identifiers can be used to reset passwords and gain access to accounts.

Is this allowed under policy or law?

Context Is it safe?
Personal experimentation Risky
Business use No
Regulated industry Definitely not
With redaction Sometimes

Safer ways to handle Biometric Data

Biometric Data should not be shared with consumer AI tools without controls in place. If AI assistance is required, organizations should use systems that enforce data redaction, access controls, and policy enforcement before data leaves their environment.

  • Automatically redact sensitive fields before sending data to AI models
  • Prevent unauthorized data from being entered into external tools
  • Maintain audit logs and visibility into how data is used
  • Ensure compliance with frameworks like GDPR, CCPA, and SOC 2

Platforms like Wald are designed to enable safe AI usage by ensuring sensitive data never leaves your control unprotected.

How Wald.ai handles this safely

Wald adds a governance layer to AI usage, helping organizations monitor and control how sensitive data like Biometric Data is shared.

AI DLP

Identifies Biometric Data in context and enables teams to:

  • Observe AI usage
  • Detect sensitive data in prompts
  • Allow, warn, or block actions
  • Maintain audit logs

LLM Pack

Provides controlled access to multiple AI models (ChatGPT, Claude, Grok, and others) through a single governed environment.

  • Centralized model access
  • Policy enforcement
  • Usage visibility
  • Auditability

Frequently Asked Questions

Is it safe to share Biometric Data with ChatGPT?
No. Biometric Data should not be shared with ChatGPT. Exposure can create security, privacy, or compliance risks, and once submitted there may be limited control over retention, logging, or downstream processing.
What happens when Biometric Data is entered into ChatGPT?
The data is transmitted to the AI provider's infrastructure for processing. Depending on the service and configuration, it may be temporarily stored, logged, or retained for security and operational purposes.
Can ChatGPT retain Biometric Data after a conversation ends?
ChatGPT providers may temporarily retain prompts and responses for security, abuse monitoring, or operational purposes. Depending on the platform and settings, Biometric Data may remain stored beyond the immediate session. In some cases, submitted data may be retained for up to 30 days before deletion. Organizations should assume that any sensitive information shared with AI systems could persist beyond the active conversation.
Does ChatGPT train on Biometric Data?
Some AI providers allow organizations to disable training on submitted data, while others may use interactions to improve services. Even when training is disabled, Biometric Data may still be processed, logged, or retained according to provider policies.
What happens if Biometric Data is accidentally shared with ChatGPT?
Once submitted, organizations may have limited visibility into how the information is retained, processed, or accessed. The appropriate response depends on the sensitivity of the data, internal policies, and incident response procedures.
Why do traditional DLP solutions struggle to identify Biometric Data in AI prompts?
Traditional DLP tools rely heavily on pattern matching and predefined rules. AI prompts often contain fragmented, transformed, or contextual information that can be difficult to classify accurately. Context-aware AI DLP solutions can evaluate surrounding context to better distinguish between similar data types and reduce false positives and false negatives.

Related questions people ask:

blog-cta-image
Secure Your Employee Conversations with AI Assistants
Book A Demo