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updatedAt: 2026-05-13T22:23:26.000Z
agentTools:
  projectIndex: https://docs.bigeye.com/llms.txt
---

# Classifiers

## How Bigeye Detects Sensitive Data

Bigeye Sensitive Data Scanning uses a combination of pattern matching, checksum validation, and machine learning to detect sensitive data across your structured data sources. These techniques work together to build confidence before a finding is produced, balancing precision with recall to minimize false positives.

All detection runs entirely within your environment. **Bigeye does not train models on your data** — classification is performed using inference only.

## Key Concepts

**Classifier:** A classifier contains the detection logic used to identify a specific type of sensitive data. Each classifier produces a single **data class** as its output when a match is found (e.g., "SSN", "Email Address", "Credit Card Number"). When configuring a classifier, you will select the data class to be applied when the classifier's detection patterns are satisfied.

**Data class:** A label that describes the type of sensitive data discovered. Each data class can be mapped to a **sensitivity level** — Public, Internal Only, Confidential, or Restricted — to indicate the level of risk associated with that data.

**Detector:** The atomic unit of detection logic within a classifier. Detectors can use regex patterns or machine learning models. When a classifier contains multiple detectors, they can be combined using AND or OR logic.

## Out-of-the-Box Classifiers

Bigeye ships with a curated set of out-of-the-box classifiers ready to use in your scan jobs. These cover common sensitive data types across PII, PHI, PCI, and financial data.

### Personally Identifiable Information (PII)

| Data Class                                | Description                                                     |
| ----------------------------------------- | --------------------------------------------------------------- |
| Name                                      | Full or partial person names                                    |
| Email Address                             | Email addresses                                                 |
| Phone Number                              | Phone numbers (USA only)                                        |
| Home or Mailing Address                   | Physical street and mailing addresses                           |
| Date of Birth                             | Dates of birth                                                  |
| Place of Birth                            | Location of birth                                               |
| Age                                       | Age values                                                      |
| Mother's Maiden Name                      | Maiden name identifiers, commonly used in security verification |
| Nationality, Religion, or Political Group | Demographic and group affiliation identifiers                   |
| Password                                  | Password fields identified by column name and value patterns    |
| Personal Account Usernames                | User account identifiers                                        |
| IP Address                                | IPv4 and IPv6 addresses                                         |
| Location                                  | General geographic or location data                             |
| Date or Datetime                          | Date and timestamp values                                       |
| Web URL                                   | Web addresses that may contain identifying information          |
| Device Identifier or Serial Number        | Hardware or device serial numbers                               |
| Crypto Wallet ID                          | Cryptocurrency wallet addresses                                 |

### Government & Travel Identifiers

| Data Class                                         | Description                                                              |
| -------------------------------------------------- | ------------------------------------------------------------------------ |
| US SSN/TIN                                         | US Social Security Numbers and Tax Identification Numbers                |
| US ITIN                                            | US Individual Taxpayer Identification Numbers                            |
| US Driver's License Number / State ID              | US driver's license and state ID numbers across all US states            |
| US Passport Number                                 | US passport numbers                                                      |
| Vehicle Identifiers (VIN, Plate #, Registration #) | Vehicle identification numbers, license plates, and registration numbers |

### Protected Health Information (PHI)

| Data Class                                  | Description                                         |
| ------------------------------------------- | --------------------------------------------------- |
| Patient Name                                | Patient name fields in healthcare contexts          |
| MRN (Medical Record Number)                 | Medical record number identifiers                   |
| Diagnosis                                   | Diagnostic codes and descriptions (e.g., ICD codes) |
| Treatment Codes                             | Medical treatment and procedure codes               |
| Medical Information                         | General medical and clinical information            |
| Medical License                             | Medical practitioner license numbers                |
| Provider NPI (National Provider Identifier) | National Provider Identifier numbers                |
| Health Plan / Insurance Number              | Health insurance and plan identifiers               |
| Healthcare Admission Date                   | Patient admission dates                             |
| Healthcare Discharge Date                   | Patient discharge dates                             |

### Payment Card Industry (PCI)

| Data Class         | Description                                            |
| ------------------ | ------------------------------------------------------ |
| Credit Card Number | Credit and debit card numbers, validated with checksum |
| CC Expiration Date | Card expiration dates                                  |
| CVV                | Card verification values                               |

### Personal Financial Information (PFI)

| Data Class             | Description                        |
| ---------------------- | ---------------------------------- |
| US Bank Account Number | US bank account numbers            |
| IBAN Code              | International Bank Account Numbers |
| Account PIN            | Account PIN codes                  |
| Credit Score           | Credit score values                |

*If the above list lacks a classifier that you need, please inform your Bigeye representative.*

## Customizing Classifiers

### Clone and Adjust

You can clone any out-of-the-box classifier to create your own version. Cloned classifiers can be adjusted — for example, modifying or adding regex patterns to better match data formats specific to your organization.

### Build from Scratch

You can also create classifiers entirely from scratch. When building a custom classifier, you can add one or more detectors using regex patterns, machine learning models, or a combination of both. Multiple detectors within a single classifier can be linked with AND or OR logic to fine-tune detection accuracy.

When creating or editing any classifier, you will assign a **data class** that will be applied as the finding output whenever the classifier's detection logic is satisfied.