Struct aws_sdk_macie2::model::ClassificationResult

#[non_exhaustive]
pub struct ClassificationResult {
    pub additional_occurrences: bool,
    pub custom_data_identifiers: Option<CustomDataIdentifiers>,
    pub mime_type: Option<String>,
    pub sensitive_data: Option<Vec<SensitiveDataItem>>,
    pub size_classified: i64,
    pub status: Option<ClassificationResultStatus>,
}

Provides the details of a sensitive data finding, including the types, number of occurrences, and locations of the sensitive data that was detected.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

additional_occurrences: bool

Specifies whether Amazon Macie detected additional occurrences of sensitive data in the S3 object. A finding includes location data for a maximum of 15 occurrences of sensitive data.

This value can help you determine whether to investigate additional occurrences of sensitive data in an object. You can do this by referring to the corresponding sensitive data discovery result for the finding (ClassificationDetails.detailedResultsLocation).

custom_data_identifiers: Option<CustomDataIdentifiers>

The custom data identifiers that detected the sensitive data and the number of occurrences of the data that they detected.

mime_type: Option<String>

The type of content, as a MIME type, that the finding applies to. For example, application/gzip, for a GNU Gzip compressed archive file, or application/pdf, for an Adobe Portable Document Format file.

sensitive_data: Option<Vec<SensitiveDataItem>>

The category, types, and number of occurrences of the sensitive data that produced the finding.

size_classified: i64

The total size, in bytes, of the data that the finding applies to.

status: Option<ClassificationResultStatus>

The status of the finding.

Implementations

impl ClassificationResult

pub fn additional_occurrences(&self) -> bool

Specifies whether Amazon Macie detected additional occurrences of sensitive data in the S3 object. A finding includes location data for a maximum of 15 occurrences of sensitive data.

This value can help you determine whether to investigate additional occurrences of sensitive data in an object. You can do this by referring to the corresponding sensitive data discovery result for the finding (ClassificationDetails.detailedResultsLocation).

pub fn custom_data_identifiers(&self) -> Option<&CustomDataIdentifiers>

The custom data identifiers that detected the sensitive data and the number of occurrences of the data that they detected.

pub fn mime_type(&self) -> Option<&str>

The type of content, as a MIME type, that the finding applies to. For example, application/gzip, for a GNU Gzip compressed archive file, or application/pdf, for an Adobe Portable Document Format file.

pub fn sensitive_data(&self) -> Option<&[SensitiveDataItem]>

The category, types, and number of occurrences of the sensitive data that produced the finding.

pub fn size_classified(&self) -> i64

The total size, in bytes, of the data that the finding applies to.

pub fn status(&self) -> Option<&ClassificationResultStatus>

The status of the finding.

impl ClassificationResult

pub fn builder() -> Builder

Creates a new builder-style object to manufacture ClassificationResult

Trait Implementations

impl Clone for ClassificationResult

fn clone(&self) -> ClassificationResult

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ClassificationResult

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq<ClassificationResult> for ClassificationResult

fn eq(&self, other: &ClassificationResult) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &ClassificationResult) -> bool

This method tests for !=.

impl StructuralPartialEq for ClassificationResult