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Detector · financial

Credit card numbers tokenization

Customer support agents paste credit card numbers into AI summarizers all the time. Cypherz catches them with Luhn validation — no false positives on random numeric strings, no PANs leaving your environment.

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  • 01

    Luhn-validated

    Only values that pass the Luhn checksum are tokenized — eliminates false positives.

  • 02

    Supports separator variations

    Handles `4111 1111 1111 1111`, `4111-1111-1111-1111`, `4111111111111111`.

  • 03

    Keeps PCI scope tight

    Your LLM vendor never receives a PAN — they cannot become part of your PCI environment.

Same input, with and without Cypherz

// Without Cypherz — the model sees real data:
Card on file: 4111 1111 1111 1111. Charge $42.50.

// With Cypherz — the model sees surrogates:
Card on file: <CC_a1b2c3d4e5f6>. Charge <AMT_d4e5f6a1b2c3>.

// The application gets the original back inside its trust boundary.

Common questions

Frequently asked.

Are credit card numbers tokens deterministic?

Yes — within a project, the same input always maps to the same surrogate token. This makes joins, dedupe, and analytics keep working on tokenized data without ever decrypting.

Can I disable this detector for a specific project?

Yes — every detector is toggleable per project at creation time and editable from the dashboard.

What if I have a custom format Cypherz doesn't recognize?

Add a custom regex or literal list per project. Cypherz applies your rules after the built-in detectors run.

Are tokenization mappings encrypted at rest?

Yes — AES-256-GCM with envelope encryption. Each project has its own data-encryption key wrapped under the master key.

Get started

Add credit card numbers protection to your AI features.

Sign up, create a project, copy your API key. The first request is tokenized in under sixty seconds.

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