PII scanners | CerbIA

cerbia.core.scanners.PiiScanner uses built-in regular expressions to locate common personally identifiable information. It reports match spans and uses the highest matching pattern score as its risk score.

Parameter Default Meaning

Parameter	Default	Meaning
`extra_patterns`	`null`	Additional `(name, regex)` pairs. Extra patterns use risk `0.80`.
`severity`	`HIGH`	Finding severity.
`action`	`WARN`	Findings are visible but do not contribute to blocking aggregation unless changed.
`content_types`	`[TEXT]`	Accepted content types.
`validate_checksums`	`false`	When `true`, candidate matches failing checksum validation are discarded (e.g. Modulo 23 for Spanish DNI/NIE, Luhn for credit cards, and Modulo 97 for IBAN). This reduces noise but can also miss sensitive identifiers with typos.
`custom_validators`	`null`	Optional dictionary mapping pattern names to custom validator callables `(str) → bool`.

extra_patterns

null

Additional (name, regex) pairs. Extra patterns use risk 0.80.

severity

HIGH

Finding severity.

action

WARN

Findings are visible but do not contribute to blocking aggregation unless changed.

content_types

[TEXT]

Accepted content types.

validate_checksums

false

When true, candidate matches failing checksum validation are discarded (e.g. Modulo 23 for Spanish DNI/NIE, Luhn for credit cards, and Modulo 97 for IBAN). This reduces noise but can also miss sensitive identifiers with typos.

custom_validators

null

Optional dictionary mapping pattern names to custom validator callables (str) → bool.

scanners:
  - scanner: cerbia.core.scanners.PiiScanner
    init_args:
      action: block
      validate_checksums: true
      extra_patterns:
        - ["Employee ID", "EMP-[0-9]{6}"]

For NLP-backed English entity recognition, use the optional PresidioPiiScanner. See the Presidio package reference.

Use action: block when detected PII must affect the aggregate verdict. Keep the default warn when the pipeline should report PII while allowing the caller to make a separate handling decision from the findings and match spans.