View Source API Reference google_api_dlp v0.46.0
Modules
API client metadata for GoogleApi.DLP.V2.
API calls for all endpoints tagged InfoTypes.
API calls for all endpoints tagged Locations.
API calls for all endpoints tagged Organizations.
API calls for all endpoints tagged Projects.
Handle Tesla connections for GoogleApi.DLP.V2.
A task to execute on the completion of a job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-actions to learn more.
The results of an Action.
Request message for ActivateJobTrigger.
Apply transformation to all findings.
Catch-all for all other tables not specified by other filters. Should always be last, except for single-table configurations, which will only have a TableReference target.
Match database resources not covered by any other filter.
Apply to all text.
Result of a risk analysis operation request.
An auxiliary table contains statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
Target used to match against for discovery with BigQuery tables
Message defining a field of a BigQuery table.
Row key for identifying a record in BigQuery table.
Options defining BigQuery table and row identifiers.
A pattern to match against one or more tables, datasets, or projects that contain BigQuery tables. At least one pattern must be specified. Regular expressions use RE2 syntax; a guide can be found under the google/re2 repository on GitHub.
A collection of regular expressions to determine what tables to match against.
Message defining the location of a BigQuery table. A table is uniquely identified by its project_id, dataset_id, and table_name. Within a query a table is often referenced with a string in the format of: :. or ...
Specifies a collection of BigQuery tables. Used for Discovery.
The types of BigQuery tables supported by Cloud DLP.
Bounding box encompassing detected text within an image.
Bucket is represented as a range, along with replacement values.
Generalization function that buckets values based on ranges. The ranges and replacement values are dynamically provided by the user for custom behavior, such as 1-30 -> LOW 31-65 -> MEDIUM 66-100 -> HIGH This can be used on data of type: number, long, string, timestamp. If the bound Value type differs from the type of data being transformed, we will first attempt converting the type of the data to be transformed to match the type of the bound before comparing. See https://cloud.google.com/sensitive-data-protection/docs/concepts-bucketing to learn more.
Container for bytes to inspect or redact.
The request message for canceling a DLP job.
Compute numerical stats over an individual column, including number of distinct values and value count distribution.
Histogram of value frequencies in the column.
Result of the categorical stats computation.
Partially mask a string by replacing a given number of characters with a fixed character. Masking can start from the beginning or end of the string. This can be used on data of any type (numbers, longs, and so on) and when de-identifying structured data we'll attempt to preserve the original data's type. (This allows you to take a long like 123 and modify it to a string like **3.
Characters to skip when doing deidentification of a value. These will be left alone and skipped.
Target used to match against for discovery with Cloud SQL tables.
Use IAM auth to connect. This requires the Cloud SQL IAM feature to be enabled on the instance, which is not the default for Cloud SQL. See https://cloud.google.com/sql/docs/postgres/authentication and https://cloud.google.com/sql/docs/mysql/authentication.
Cloud SQL connection properties.
Message representing a set of files in Cloud Storage.
Options defining a file or a set of files within a Cloud Storage bucket.
Message representing a single file or path in Cloud Storage.
Message representing a set of files in a Cloud Storage bucket. Regular expressions are used to allow fine-grained control over which files in the bucket to include. Included files are those that match at least one item in include_regex and do not match any items in exclude_regex. Note that a file that matches items from both lists will not be included. For a match to occur, the entire file path (i.e., everything in the url after the bucket name) must match the regular expression. For example, given the input {bucket_name: "mybucket", include_regex: ["directory1/.*"], exclude_regex: ["directory1/excluded.*"]}: gs://mybucket/directory1/myfile will be included gs://mybucket/directory1/directory2/myfile will be included (.* matches across /) gs://mybucket/directory0/directory1/myfile will not be included (the full path doesn't match any items in include_regex) gs://mybucket/directory1/excludedfile will not be included (the path matches an item in exclude_regex) If include_regex is left empty, it will match all files by default (this is equivalent to setting include_regex: [".*"]). Some other common use cases: `{bucket_name: "mybucket", exclude_regex: ["..pdf"]}will include all files inmybucketexcept for .pdf files *{bucket_name: "mybucket", include_regex: ["directory/[^/]+"]}will include all files directly undergs://mybucket/directory/, without matching across/`
Represents a color in the RGB color space.
The profile for a scanned column within a table.
The field type of value and field do not need to match to be considered equal, but not all comparisons are possible. EQUAL_TO and NOT_EQUAL_TO attempt to compare even with incompatible types, but all other comparisons are invalid with incompatible types. A value of type: - string can be compared against all other types - boolean can only be compared against other booleans - integer can be compared against doubles or a string if the string value can be parsed as an integer. - double can be compared against integers or a string if the string can be parsed as a double. - Timestamp can be compared against strings in RFC 3339 date string format. - TimeOfDay can be compared against timestamps and strings in the format of 'HH:mm:ss'. If we fail to compare do to type mismatch, a warning will be given and the condition will evaluate to false.
A collection of conditions.
A data connection to allow DLP to profile data in locations that require additional configuration.
Represents a container that may contain DLP findings. Examples of a container include a file, table, or database record.
Type of content to inspect.
Precise location of the finding within a document, record, image, or metadata container.
Request message for CreateConnection.
Request message for CreateDeidentifyTemplate.
Request message for CreateDiscoveryConfig.
Request message for CreateDlpJobRequest. Used to initiate long running jobs such as calculating risk metrics or inspecting Google Cloud Storage.
Request message for CreateInspectTemplate.
Request message for CreateJobTrigger.
Request message for CreateStoredInfoType.
Pseudonymization method that generates deterministic encryption for the given input. Outputs a base64 encoded representation of the encrypted output. Uses AES-SIV based on the RFC https://tools.ietf.org/html/rfc5297.
Pseudonymization method that generates surrogates via cryptographic hashing. Uses SHA-256. The key size must be either 32 or 64 bytes. Outputs a base64 encoded representation of the hashed output (for example, L7k0BHmF1ha5U3NfGykjro4xWi1MPVQPjhMAZbSV9mM=). Currently, only string and integer values can be hashed. See https://cloud.google.com/sensitive-data-protection/docs/pseudonymization to learn more.
This is a data encryption key (DEK) (as opposed to a key encryption key (KEK) stored by Cloud Key Management Service (Cloud KMS). When using Cloud KMS to wrap or unwrap a DEK, be sure to set an appropriate IAM policy on the KEK to ensure an attacker cannot unwrap the DEK.
Replaces an identifier with a surrogate using Format Preserving Encryption (FPE) with the FFX mode of operation; however when used in the ReidentifyContent API method, it serves the opposite function by reversing the surrogate back into the original identifier. The identifier must be encoded as ASCII. For a given crypto key and context, the same identifier will be replaced with the same surrogate. Identifiers must be at least two characters long. In the case that the identifier is the empty string, it will be skipped. See https://cloud.google.com/sensitive-data-protection/docs/pseudonymization to learn more. Note: We recommend using CryptoDeterministicConfig for all use cases which do not require preserving the input alphabet space and size, plus warrant referential integrity.
Custom information type provided by the user. Used to find domain-specific sensitive information configurable to the data in question.
A task to execute when a data profile has been generated.
The schema of data to be saved to the BigQuery table when the DataProfileAction is enabled.
Snapshot of the configurations used to generate the profile.
Configuration for setting up a job to scan resources for profile generation. Only one data profile configuration may exist per organization, folder, or project. The generated data profiles are retained according to the [data retention policy] (https://cloud.google.com/sensitive-data-protection/docs/data-profiles#retention).
The data that will be profiled.
A condition for determining whether a Pub/Sub should be triggered.
Pub/Sub topic message for a DataProfileAction.PubSubNotification event. To receive a message of protocol buffer schema type, convert the message data to an object of this proto class.
Score is a summary of all elements in the data profile. A higher number means more risk.
Message used to identify the type of resource being profiled.
Match database resources using regex filters. Examples of database resources are tables, views, and stored procedures.
Identifies a single database resource, like a table within a database.
A pattern to match against one or more database resources. At least one pattern must be specified. Regular expressions use RE2 syntax; a guide can be found under the google/re2 repository on GitHub.
A collection of regular expressions to determine what database resources to match against.
Record key for a finding in Cloud Datastore.
Options defining a data set within Google Cloud Datastore.
Shifts dates by random number of days, with option to be consistent for the same context. See https://cloud.google.com/sensitive-data-protection/docs/concepts-date-shifting to learn more.
Message for a date time object. e.g. 2018-01-01, 5th August.
Create a de-identified copy of the requested table or files. A TransformationDetail will be created for each transformation. If any rows in BigQuery are skipped during de-identification (transformation errors or row size exceeds BigQuery insert API limits) they are placed in the failure output table. If the original row exceeds the BigQuery insert API limit it will be truncated when written to the failure output table. The failure output table can be set in the action.deidentify.output.big_query_output.deidentified_failure_output_table field, if no table is set, a table will be automatically created in the same project and dataset as the original table. Compatible with: Inspect
The configuration that controls how the data will change.
Request to de-identify a ContentItem.
Results of de-identifying a ContentItem.
The results of a Deidentify action from an inspect job.
Summary of what was modified during a transformation.
DeidentifyTemplates contains instructions on how to de-identify content. See https://cloud.google.com/sensitive-data-protection/docs/concepts-templates to learn more.
δ-presence metric, used to estimate how likely it is for an attacker to figure out that one given individual appears in a de-identified dataset. Similarly to the k-map metric, we cannot compute δ-presence exactly without knowing the attack dataset, so we use a statistical model instead.
A DeltaPresenceEstimationHistogramBucket message with the following values: min_probability: 0.1 max_probability: 0.2 frequency: 42 means that there are 42 records for which δ is in [0.1, 0.2). An important particular case is when min_probability = max_probability = 1: then, every individual who shares this quasi-identifier combination is in the dataset.
A tuple of values for the quasi-identifier columns.
Result of the δ-presence computation. Note that these results are an estimation, not exact values.
Deprecated; use InspectionRuleSet instead. Rule for modifying a CustomInfoType to alter behavior under certain circumstances, depending on the specific details of the rule. Not supported for the surrogate_type custom infoType.
Custom information type based on a dictionary of words or phrases. This can be used to match sensitive information specific to the data, such as a list of employee IDs or job titles. Dictionary words are case-insensitive and all characters other than letters and digits in the unicode Basic Multilingual Plane will be replaced with whitespace when scanning for matches, so the dictionary phrase "Sam Johnson" will match all three phrases "sam johnson", "Sam, Johnson", and "Sam (Johnson)". Additionally, the characters surrounding any match must be of a different type than the adjacent characters within the word, so letters must be next to non-letters and digits next to non-digits. For example, the dictionary word "jen" will match the first three letters of the text "jen123" but will return no matches for "jennifer". Dictionary words containing a large number of characters that are not letters or digits may result in unexpected findings because such characters are treated as whitespace. The limits page contains details about the size limits of dictionaries. For dictionaries that do not fit within these constraints, consider using LargeCustomDictionaryConfig in the StoredInfoType API.
Do not profile the tables.
Requirements that must be true before a table is scanned in discovery for the first time. There is an AND relationship between the top-level attributes. Additionally, minimum conditions with an OR relationship that must be met before Cloud DLP scans a table can be set (like a minimum row count or a minimum table age).
Determines what tables will have profiles generated within an organization or project. Includes the ability to filter by regular expression patterns on project ID, dataset ID, and table ID.
Requirements that must be true before a table is profiled for the first time.
Determines what tables will have profiles generated within an organization or project. Includes the ability to filter by regular expression patterns on project ID, location, instance, database, and database resource name.
How often existing tables should have their profiles refreshed. New tables are scanned as quickly as possible depending on system capacity.
Configuration for discovery to scan resources for profile generation. Only one discovery configuration may exist per organization, folder, or project. The generated data profiles are retained according to the [data retention policy] (https://cloud.google.com/sensitive-data-protection/docs/data-profiles#retention).
What must take place for a profile to be updated and how frequently it should occur. New tables are scanned as quickly as possible depending on system capacity.
The cadence at which to update data profiles when a schema is modified.
The location to begin a discovery scan. Denotes an organization ID or folder ID within an organization.
The cadence at which to update data profiles when a table is modified.
Target used to match against for Discovery.
Combines all of the information about a DLP job.
Location of a finding within a document.
An entity in a dataset is a field or set of fields that correspond to a single person. For example, in medical records the EntityId might be a patient identifier, or for financial records it might be an account identifier. This message is used when generalizations or analysis must take into account that multiple rows correspond to the same entity.
Details information about an error encountered during job execution or the results of an unsuccessful activation of the JobTrigger.
The rule to exclude findings based on a hotword. For record inspection of tables, column names are considered hotwords. An example of this is to exclude a finding if it belongs to a BigQuery column that matches a specific pattern.
List of excluded infoTypes.
The rule that specifies conditions when findings of infoTypes specified in InspectionRuleSet are removed from results.
If set, the detailed data profiles will be persisted to the location of your choice whenever updated.
An expression, consisting of an operator and conditions.
General identifier of a data field in a storage service.
The transformation to apply to the field.
Set of files to scan.
Represents a piece of potentially sensitive content.
Configuration to control the number of findings returned for inspection. This is not used for de-identification or data profiling. When redacting sensitive data from images, finding limits don't apply. They can cause unexpected or inconsistent results, where only some data is redacted. Don't include finding limits in RedactImage requests. Otherwise, Cloud DLP returns an error.
The request message for finishing a DLP hybrid job.
Buckets values based on fixed size ranges. The Bucketing transformation can provide all of this functionality, but requires more configuration. This message is provided as a convenience to the user for simple bucketing strategies. The transformed value will be a hyphenated string of {lower_bound}-{upper_bound}. For example, if lower_bound = 10 and upper_bound = 20, all values that are within this bucket will be replaced with "10-20". This can be used on data of type: double, long. If the bound Value type differs from the type of data being transformed, we will first attempt converting the type of the data to be transformed to match the type of the bound before comparing. See https://cloud.google.com/sensitive-data-protection/docs/concepts-bucketing to learn more.
The rule that adjusts the likelihood of findings within a certain proximity of hotwords.
An individual hybrid item to inspect. Will be stored temporarily during processing.
Populate to associate additional data with each finding.
Request to search for potentially sensitive info in a custom location.
Request to search for potentially sensitive info in a custom location.
Quota exceeded errors will be thrown once quota has been met.
Statistics related to processing hybrid inspect requests.
Configuration to control jobs where the content being inspected is outside of Google Cloud Platform.
Location of the finding within an image.
Configuration for determining how redaction of images should occur.
Configuration for determining how redaction of images should occur.
A type of transformation that is applied over images.
Type of information detected by the API.
Classification of infoTypes to organize them according to geographic location, industry, and data type.
InfoType description.
Configuration for setting a minimum likelihood per infotype. Used to customize the minimum likelihood level for specific infotypes in the request. For example, use this if you want to lower the precision for PERSON_NAME without lowering the precision for the other infotypes in the request.
Max findings configuration per infoType, per content item or long running DlpJob.
Statistics regarding a specific InfoType.
The infoType details for this column.
A transformation to apply to text that is identified as a specific info_type.
A type of transformation that will scan unstructured text and apply various PrimitiveTransformations to each finding, where the transformation is applied to only values that were identified as a specific info_type.
Configuration description of the scanning process. When used with redactContent only info_types and min_likelihood are currently used.
Request to search for potentially sensitive info in a ContentItem.
Results of inspecting an item.
The results of an inspect DataSource job.
Controls what and how to inspect for findings.
All the findings for a single scanned item.
The inspectTemplate contains a configuration (set of types of sensitive data to be detected) to be used anywhere you otherwise would normally specify InspectConfig. See https://cloud.google.com/sensitive-data-protection/docs/concepts-templates to learn more.
A single inspection rule to be applied to infoTypes, specified in InspectionRuleSet.
Rule set for modifying a set of infoTypes to alter behavior under certain circumstances, depending on the specific details of the rules within the set.
Sends an email when the job completes. The email goes to IAM project owners and technical Essential Contacts.
Contains a configuration to make api calls on a repeating basis. See https://cloud.google.com/sensitive-data-protection/docs/concepts-job-triggers to learn more.
k-anonymity metric, used for analysis of reidentification risk.
The set of columns' values that share the same ldiversity value
Histogram of k-anonymity equivalence classes.
Result of the k-anonymity computation.
Reidentifiability metric. This corresponds to a risk model similar to what is called "journalist risk" in the literature, except the attack dataset is statistically modeled instead of being perfectly known. This can be done using publicly available data (like the US Census), or using a custom statistical model (indicated as one or several BigQuery tables), or by extrapolating from the distribution of values in the input dataset.
A KMapEstimationHistogramBucket message with the following values: min_anonymity: 3 max_anonymity: 5 frequency: 42 means that there are 42 records whose quasi-identifier values correspond to 3, 4 or 5 people in the overlying population. An important particular case is when min_anonymity = max_anonymity = 1: the frequency field then corresponds to the number of uniquely identifiable records.
A tuple of values for the quasi-identifier columns.
Result of the reidentifiability analysis. Note that these results are an estimation, not exact values.
A unique identifier for a Datastore entity. If a key's partition ID or any of its path kinds or names are reserved/read-only, the key is reserved/read-only. A reserved/read-only key is forbidden in certain documented contexts.
A representation of a Datastore kind.
Include to use an existing data crypto key wrapped by KMS. The wrapped key must be a 128-, 192-, or 256-bit key. Authorization requires the following IAM permissions when sending a request to perform a crypto transformation using a KMS-wrapped crypto key: dlp.kms.encrypt For more information, see [Creating a wrapped key] (https://cloud.google.com/sensitive-data-protection/docs/create-wrapped-key). Note: When you use Cloud KMS for cryptographic operations, charges apply.
l-diversity metric, used for analysis of reidentification risk.
The set of columns' values that share the same ldiversity value.
Histogram of l-diversity equivalence class sensitive value frequencies.
Result of the l-diversity computation.
Configuration for a custom dictionary created from a data source of any size up to the maximum size defined in the limits page. The artifacts of dictionary creation are stored in the specified Cloud Storage location. Consider using CustomInfoType.Dictionary for smaller dictionaries that satisfy the size requirements.
Summary statistics of a custom dictionary.
Skips the data without modifying it if the requested transformation would cause an error. For example, if a DateShift transformation were applied an an IP address, this mode would leave the IP address unchanged in the response.
Message for specifying an adjustment to the likelihood of a finding as part of a detection rule.
List of profiles generated for a given organization or project.
Response message for ListConnections.
Response message for ListDeidentifyTemplates.
Response message for ListDiscoveryConfigs.
The response message for listing DLP jobs.
Response to the ListInfoTypes request.
Response message for ListInspectTemplates.
Response message for ListJobTriggers.
List of profiles generated for a given organization or project.
Response message for ListStoredInfoTypes.
List of profiles generated for a given organization or project.
Specifies the location of the finding.
Job trigger option for hybrid jobs. Jobs must be manually created and finished.
Metadata Location
Compute numerical stats over an individual column, including min, max, and quantiles.
Result of the numerical stats computation.
There is an OR relationship between these attributes. They are used to determine if a table should be scanned or not in Discovery.
Project and scan location information. Only set when the parent is an org.
Infotype details for other infoTypes found within a column.
Cloud repository for storing output.
Datastore partition ID. A partition ID identifies a grouping of entities. The grouping is always by project and namespace, however the namespace ID may be empty. A partition ID contains several dimensions: project ID and namespace ID.
A (kind, ID/name) pair used to construct a key path. If either name or ID is set, the element is complete. If neither is set, the element is incomplete.
A rule for transforming a value.
Privacy metric to compute for reidentification risk analysis.
Success or errors for the profile generation.
An aggregated profile for this project, based on the resources profiled within it.
Message for specifying a window around a finding to apply a detection rule.
A condition consisting of a value.
An expression, consisting of an operator and conditions.
Send a Pub/Sub message into the given Pub/Sub topic to connect other systems to data profile generation. The message payload data will be the byte serialization of DataProfilePubSubMessage.
Publish findings of a DlpJob to Data Catalog. In Data Catalog, tag templates are applied to the resource that Cloud DLP scanned. Data Catalog tag templates are stored in the same project and region where the BigQuery table exists. For Cloud DLP to create and apply the tag template, the Cloud DLP service agent must have the roles/datacatalog.tagTemplateOwner permission on the project. The tag template contains fields summarizing the results of the DlpJob. Any field values previously written by another DlpJob are deleted. InfoType naming patterns are strictly enforced when using this feature. Findings are persisted in Data Catalog storage and are governed by service-specific policies for Data Catalog. For more information, see Service Specific Terms. Only a single instance of this action can be specified. This action is allowed only if all resources being scanned are BigQuery tables. Compatible with: Inspect
Publish the result summary of a DlpJob to Security Command Center. This action is available for only projects that belong to an organization. This action publishes the count of finding instances and their infoTypes. The summary of findings are persisted in Security Command Center and are governed by service-specific policies for Security Command Center. Only a single instance of this action can be specified. Compatible with: Inspect
Publish a message into a given Pub/Sub topic when DlpJob has completed. The message contains a single field, DlpJobName, which is equal to the finished job's DlpJob.name. Compatible with: Inspect, Risk
Enable Stackdriver metric dlp.googleapis.com/finding_count. This will publish a metric to stack driver on each infotype requested and how many findings were found for it. CustomDetectors will be bucketed as 'Custom' under the Stackdriver label 'info_type'.
A column with a semantic tag attached.
A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
A quasi-identifier column has a custom_tag, used to know which column in the data corresponds to which column in the statistical model.
Message for infoType-dependent details parsed from quote.
Generic half-open interval [start, end)
A condition for determining whether a transformation should be applied to a field.
Message for a unique key indicating a record that contains a finding.
Location of a finding within a row or record.
Configuration to suppress records whose suppression conditions evaluate to true.
The field in a record to transform.
A type of transformation that is applied over structured data such as a table.
Redact a given value. For example, if used with an InfoTypeTransformation transforming PHONE_NUMBER, and input 'My phone number is 206-555-0123', the output would be 'My phone number is '.
Request to search for potentially sensitive info in an image and redact it by covering it with a colored rectangle.
Results of redacting an image.
Message defining a custom regular expression.
Request to re-identify an item.
Results of re-identifying an item.
Replace each input value with a value randomly selected from the dictionary.
Replace each input value with a given Value.
Replace each matching finding with the name of the info_type.
De-identification options.
Snapshot of the inspection configuration.
Risk analysis options.
All result fields mentioned below are updated while the job is processing.
Configuration for a risk analysis job. See https://cloud.google.com/sensitive-data-protection/docs/concepts-risk-analysis to learn more.
Values of the row.
If set, the detailed findings will be persisted to the specified OutputStorageConfig. Only a single instance of this action can be specified. Compatible with: Inspect, Risk
Schedule for inspect job triggers.
How frequency to modify the profile when the table's schema is modified.
Response message for SearchConnections.
A credential consisting of a username and password, where the password is stored in a Secret Manager resource. Note: Secret Manager charges apply.
Apply transformation to the selected info_types.
Score is calculated from of all elements in the data profile. A higher level means the data is more sensitive.
An auxiliary table containing statistical information on the relative frequency of different quasi-identifiers values. It has one or several quasi-identifiers columns, and one column that indicates the relative frequency of each quasi-identifier tuple. If a tuple is present in the data but not in the auxiliary table, the corresponding relative frequency is assumed to be zero (and thus, the tuple is highly reidentifiable).
Shared message indicating Cloud storage type.
Storage metadata label to indicate which metadata entry contains findings.
StoredInfoType resource message that contains information about the current version and any pending updates.
Configuration for stored infoTypes. All fields and subfield are provided by the user. For more information, see https://cloud.google.com/sensitive-data-protection/docs/creating-custom-infotypes.
Statistics for a StoredInfoType.
Version of a StoredInfoType, including the configuration used to build it, create timestamp, and current state.
A reference to a StoredInfoType to use with scanning.
A collection that informs the user the number of times a particular TransformationResultCode and error details occurred.
Message for detecting output from deidentification transformations such as CryptoReplaceFfxFpeConfig. These types of transformations are those that perform pseudonymization, thereby producing a "surrogate" as output. This should be used in conjunction with a field on the transformation such as surrogate_info_type. This CustomInfoType does not support the use of detection_rules.
Structured content to inspect. Up to 50,000 Values per request allowed. See https://cloud.google.com/sensitive-data-protection/docs/inspecting-structured-text#inspecting_a_table to learn more.
The profile for a scanned table.
Location of a finding within a table.
Instructions regarding the table content being inspected.
A column with a semantic tag attached.
Throw an error and fail the request when a transformation error occurs.
For use with Date, Timestamp, and TimeOfDay, extract or preserve a portion of the value.
Time zone of the date time object.
Configuration of the timespan of the items to include in scanning. Currently only supported when inspecting Cloud Storage and BigQuery.
User specified templates and configs for how to deidentify structured, unstructures, and image files. User must provide either a unstructured deidentify template or at least one redact image config.
A flattened description of a PrimitiveTransformation or RecordSuppression.
Details about a single transformation. This object contains a description of the transformation, information about whether the transformation was successfully applied, and the precise location where the transformation occurred. These details are stored in a user-specified BigQuery table.
Config for storing transformation details.
How to handle transformation errors during de-identification. A transformation error occurs when the requested transformation is incompatible with the data. For example, trying to de-identify an IP address using a DateShift transformation would result in a transformation error, since date info cannot be extracted from an IP address. Information about any incompatible transformations, and how they were handled, is returned in the response as part of the TransformationOverviews.
Specifies the location of a transformation.
Overview of the modifications that occurred.
The outcome of a transformation.
Summary of a single transformation. Only one of 'transformation', 'field_transformation', or 'record_suppress' will be set.
Use this to have a random data crypto key generated. It will be discarded after the request finishes.
What event needs to occur for a new job to be started.
Using raw keys is prone to security risks due to accidentally leaking the key. Choose another type of key if possible.
Request message for UpdateConnection.
Request message for UpdateDeidentifyTemplate.
Request message for UpdateDiscoveryConfig.
Request message for UpdateInspectTemplate.
Request message for UpdateJobTrigger.
Request message for UpdateStoredInfoType.
Set of primitive values supported by the system. Note that for the purposes of inspection or transformation, the number of bytes considered to comprise a 'Value' is based on its representation as a UTF-8 encoded string. For example, if 'integer_value' is set to 123456789, the number of bytes would be counted as 9, even though an int64 only holds up to 8 bytes of data.
A value of a field, including its frequency.
Details about each available version for an infotype.
Message defining a list of words or phrases to search for in the data.
A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide.
Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: A full date, with non-zero year, month, and day values. A month and day, with a zero year (for example, an anniversary). A year on its own, with a zero month and a zero day. A year and month, with a zero day (for example, a credit card expiration date). Related types: google.type.TimeOfDay google.type.DateTime * google.protobuf.Timestamp
Represents a time of day. The date and time zone are either not significant or are specified elsewhere. An API may choose to allow leap seconds. Related types are google.type.Date and google.protobuf.Timestamp.