이제 Cloud Data Loss Prevention(Cloud DLP)은 민감한 정보 보호에 포함됩니다. API 이름은 Cloud Data Loss Prevention API(DLP API)로 그대로 유지됩니다. 민감한 정보 보호를 구성하는 서비스에 대한 자세한 내용은 민감한 정보 보호 개요를 참조하세요.
스토리지 저장소에 저장된 민감한 정보를 적절히 관리하는 일의 시작은 스토리지 분류입니다. 이를 통해 저장소에서 민감한 정보가 있는 위치, 민감한 정보의 유형, 사용되는 방법을 식별하는 것입니다. 이러한 정보는 액세스 제어 및 공유 권한을 적절히 설정하는 데 유용하며, 이는 지속적인 모니터링 계획에 포함될 수 있습니다.
민감한 정보 보호는 Cloud Storage 위치, Datastore 종류, BigQuery 테이블에 저장된 민감한 정보를 감지 및 분류할 수 있습니다. Cloud Storage 위치에서 파일을 스캔할 때 민감한 정보 보호는 바이너리, 텍스트, 이미지, Microsoft Word, Microsoft Excel, Microsoft PowerPoint, PDF, Apache Avro 파일의 스캔을 지원합니다. 인식되지 않는 형식의 파일은 바이너리 파일로 스캔됩니다. 지원되는 파일 형식에 대한 자세한 내용은 지원되는 파일 형식을 참조하세요.
스토리지와 데이터베이스에서 민감한 정보를 검사하려면 데이터 위치와 민감한 정보 보호가 찾아야 하는 민감한 정보 유형을 지정합니다. 민감한 정보 보호는 지정된 위치에서 데이터를 검사하는 작업을 시작한 다음 콘텐츠에서 발견된 infoType, 가능성 값 등에 관한 세부정보를 제공합니다.
Google Cloud 콘솔에서 민감한 정보 보호를 사용하거나 RESTful Cloud DLP API를 통해 또는 여러 언어 중 하나로 된 민감한 정보 보호 클라이언트 라이브러리를 사용하여 프로그래매틱 방식으로 스토리지 및 데이터베이스 검사를 설정할 수 있습니다.
이 주제에서 다루는 사항은 다음과 같습니다.
Google Cloud Storage 저장소 및 데이터베이스 스캔 설정을 위한 권장 사항
Google Cloud 콘솔에서 민감한 정보 보호를 사용하여 검사 스캔을 설정하는 방법과 (선택적으로) 주기적인 반복 검사 스캔을 예약하는 방법에 대한 안내입니다.
각 Google Cloud 스토리지 저장소 유형의 JSON 및 코드 샘플: (Cloud Storage, Datastore 모드의 Firestore(Datastore), BigQuery)
스캔 작업을 위한 구성 옵션의 세부적인 개요
각각의 성공적인 요청에서 생성되는 스캔 작업을 관리하는 방법과 스캔 결과를 가져오는 방법에 관한 안내
권장사항
스캔 식별 및 우선순위 지정
애셋을 평가하고 스캔 우선순위가 가장 높은 애셋을 지정하는 것이 중요합니다. 시작하기 전에 분류가 필요한 대량의 데이터 백로그가 있을 수 있으며 이 경우 즉시 스캔할 수 없습니다. 처음에는 자주 액세스하는 데이터, 폭넓게 액세스하는 데이터, 알 수 없는 데이터 등 잠재적 위험도가 가장 높은 데이터를 선택합니다.
민감한 정보 보호가 데이터에 액세스할 수 있는지 확인
민감한 정보 보호는 스캔할 데이터에 액세스할 수 있어야 합니다. 민감한 정보 보호 서비스 계정에서 리소스를 읽을 수 있는지 확인합니다.
첫 번째 스캔의 범위 제한
최상의 결과를 얻으려면 모든 데이터를 스캔하는 대신 첫 번째 작업의 범위를 제한합니다. 하나의 테이블, 하나의 버킷, 몇 개의 파일로 시작하고 샘플링을 사용합니다. 첫 번째 스캔의 범위를 제한하면 보다 의미 있는 결과를 얻기 위해 사용 설정할 감지기와 거짓양성을 줄이기 위해 필요한 제외 규칙을 더 잘 파악할 수 있습니다. 거짓양성이나 쓸모 없는 발견 항목으로 인해 위험을 평가하기 어려울 수 있으므로 모두 필요한 경우가 아니라면 모든 infoType을 사용 설정하지 마세요. 특정 시나리오에서는 유용하지만 DATE, TIME, DOMAIN_NAME, URL 같은 infoType은 광범위한 발견 항목과 일치하므로 대규모 데이터 스캔에 사용하는 경우 유용하지 않을 수 있습니다.
구조화된 파일(예: CSV, TSV 또는 Avro 파일)을 샘플링할 때 샘플 크기가 파일의 전체 헤더와 데이터 행을 포함할 만큼 충분히 큰지 확인합니다. 자세한 내용은 구조화된 파싱 모드에서 구조화된 파일 스캔을 참조하세요.
스캔 예약
민감한 정보 보호 작업 트리거를 사용하여 매일, 매주, 분기별로 스캔을 자동으로 실행하고 발견 항목을 생성합니다.
이러한 스캔은 마지막 스캔 이후 변경된 데이터만 검사하도록 구성할 수 있으므로 시간을 절약하고 비용을 줄일 수 있습니다. 정기적으로 스캔을 실행하면 스캔 결과에서 트렌드나 이상치를 식별하는 데 도움이 됩니다.
작업 지연 시간
작업 및 작업 트리거에 대한 서비스 수준 목표(SLO)가 보장되지 않습니다. 지연 시간은 스캔할 데이터 양, 스캔하는 스토리지 저장소, 스캔하는 infoType 유형 및 개수, 작업이 처리되는 리전, 사용 가능한 컴퓨팅 리소스를 포함한 여러 요인의 영향을 받습니다. 따라서 검사 작업의 지연 시간을 미리 확인할 수 없습니다.
스토리지 분류에는 다음 OAuth 범위가 필요합니다. https://www.googleapis.com/auth/cloud-platform 자세한 내용은 DLP API 인증을 참조하세요.
Cloud Storage 위치 검사
Google Cloud 콘솔을 사용하거나 DLP API에서 REST 또는 RPC 요청을 통해 또는 클라이언트 라이브러리를 사용하여 여러 언어의 프로그래매틱 방식으로 Cloud Storage 위치의 민감한 정보 보호 검사를 설정할 수 있습니다. 다음 JSON 및 코드 샘플에 포함된 매개변수에 대한 자세한 내용은 이 주제 뒷부분의 '스토리지 검사 구성'을 참조하세요.
민감한 정보 보호는 파일 확장자와 미디어(MIME) 유형을 사용하여 스캔할 파일의 유형과 적용할 스캔 모드를 식별합니다. 예를 들어 민감한 정보 보호는 파일이 일반적으로 구조화된 파싱 모드로 스캔되는 CSV 파일로 구성되어 있더라도 일반 텍스트 모드로 .txt 파일을 스캔합니다.
민감한 정보 보호를 사용하여 Cloud Storage 버킷의 스캔 작업을 설정하려면 다음 안내를 따르세요.
1단계: 입력 데이터 선택에서 이름 필드에 값을 입력하여 작업 이름을 지정합니다. 위치의 스토리지 유형 메뉴에서 Cloud Storage를 선택한 다음 스캔할 데이터의 위치를 입력합니다.
샘플링 섹션은 데이터에 대해 샘플 스캔을 실행하도록 미리 구성됩니다. 데이터가 많은 경우 버킷 내에서 스캔되는 객체 비율 필드를 조정하여 리소스를 저장할 수 있습니다. 자세한 내용은 입력 데이터 선택을 참조하세요.
(선택사항) 2단계: 감지 구성에서는 'infoType'이라고 하는 검색할 데이터 유형을 구성할 수 있습니다. 사전 정의된 infoType 목록에서 선택하거나 템플릿(있는 경우)을 선택할 수 있습니다. 자세한 내용은 감지 구성을 참조하세요.
(선택사항) 3단계: 액션 추가에서는 이메일 알림이 사용 설정되어 있는지 확인합니다.
BigQuery에 저장을 사용 설정하여 민감한 정보 보호 발견 항목을 BigQuery 테이블에 게시합니다.
다음을 제공합니다.
프로젝트 ID에 결과가 저장된 프로젝트 ID를 입력합니다.
데이터 세트 ID에 결과를 저장하는 데이터 세트 이름을 입력합니다.
(선택사항) 테이블 ID에 결과를 저장하는 테이블 이름을 입력합니다. 테이블 ID를 지정하지 않으면 새로운 테이블에는 dlp_googleapis_[DATE]_1234567890 같은 기본 이름이 할당됩니다. 여기서 [DATE]는 스캔이 실행되는 날짜를 나타냅니다. 기존 테이블을 지정하면 여기에 발견 항목이 추가됩니다.
(선택사항) infoType 감지기와 일치하는 문자열을 포함하려면 인용 포함을 사용 설정합니다. 인용은 민감할 수 있으므로 기본적으로 민감한 정보 보호에서는 인용을 발견 항목에 포함하지 않습니다.
Pub/Sub, Security Command Center, Data Catalog, Cloud Monitoring에 결과를 저장할 수도 있습니다. 자세한 내용은 액션 추가를 참조하세요.
(선택사항) 4단계: 일정에서 스캔을 한 번만 실행하려면 메뉴를 없음으로 설정합니다. 스캔이 주기적으로 실행되도록 예약하려면 주기적인 일정으로 작업을 실행하는 트리거 만들기를 클릭합니다. 자세한 내용은 일정을 참조하세요.
만들기를 클릭합니다.
민감한 정보 보호 작업이 완료되면 작업 세부정보 페이지로 리디렉션되고 이메일로 알림을 받습니다. 작업 세부정보 페이지에서 검사 결과를 볼 수 있습니다.
(선택사항) 민감한 정보 보호 발견 항목을 BigQuery에 게시하도록 선택한 경우 작업 세부정보 페이지에서 BigQuery에서 발견 항목 보기를 클릭하여 BigQuery 웹 UI로 테이블을 엽니다. 그런 다음 테이블을 쿼리하고 발견 항목을 분석할 수 있습니다. BigQuery에서 결과를 쿼리하는 방법에 대한 자세한 내용은 BigQuery에서 민감한 정보 보호 발견 항목 쿼리를 참조하세요.
프로토콜
다음은 지정된 민감한 정보 보호 REST 엔드포인트를 대상으로 한 POST 요청으로 전송할 수 있는 샘플 JSON입니다. 이 JSON 예는 DLP API를 사용하여 Cloud Storage 버킷을 검사하는 방법을 보여줍니다. 요청에 포함된 매개변수에 대한 자세한 내용은 이 주제 뒷부분의 '스토리지 검사 구성'을 참조하세요.
content.inspect의 참조 페이지에서 API 탐색기로 이를 빠르게 시도해 볼 수 있습니다.
API 탐색기에서도 요청이 성공하면 새 스캔 작업이 생성됩니다. 스캔 작업을 제어하는 방법에 대한 자세한 내용은 이 주제 뒷부분의 '검사 결과 가져오기'를 참조하세요. JSON을 사용하여 DLP API로 요청을 전송하는 데 대한 일반적인 정보는 JSON 빠른 시작을 참조하세요.
import com.google.api.core.SettableApiFuture;
import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
import com.google.cloud.pubsub.v1.MessageReceiver;
import com.google.cloud.pubsub.v1.Subscriber;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.CloudStorageOptions;
import com.google.privacy.dlp.v2.CloudStorageOptions.FileSet;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DlpJob;
import com.google.privacy.dlp.v2.GetDlpJobRequest;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeStats;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectDataSourceDetails;
import com.google.privacy.dlp.v2.InspectJobConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.StorageConfig;
import com.google.pubsub.v1.ProjectSubscriptionName;
import com.google.pubsub.v1.PubsubMessage;
import java.io.IOException;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
import java.util.stream.Collectors;
import java.util.stream.Stream;
public class InspectGcsFile {
public static void main(String[] args) throws Exception {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
String gcsUri = "gs://" + "your-bucket-name" + "/path/to/your/file.txt";
String topicId = "your-pubsub-topic-id";
String subscriptionId = "your-pubsub-subscription-id";
inspectGcsFile(projectId, gcsUri, topicId, subscriptionId);
}
// Inspects a file in a Google Cloud Storage Bucket.
public static void inspectGcsFile(
String projectId, String gcsUri, String topicId, String subscriptionId)
throws ExecutionException, InterruptedException, IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (DlpServiceClient dlp = DlpServiceClient.create()) {
// Specify the GCS file to be inspected.
CloudStorageOptions cloudStorageOptions =
CloudStorageOptions.newBuilder().setFileSet(FileSet.newBuilder().setUrl(gcsUri)).build();
StorageConfig storageConfig =
StorageConfig.newBuilder().setCloudStorageOptions(cloudStorageOptions).build();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
List<InfoType> infoTypes =
Stream.of("PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD_NUMBER")
.map(it -> InfoType.newBuilder().setName(it).build())
.collect(Collectors.toList());
// Specify how the content should be inspected.
InspectConfig inspectConfig =
InspectConfig.newBuilder().addAllInfoTypes(infoTypes).setIncludeQuote(true).build();
// Specify the action that is triggered when the job completes.
String pubSubTopic = String.format("projects/%s/topics/%s", projectId, topicId);
Action.PublishToPubSub publishToPubSub =
Action.PublishToPubSub.newBuilder().setTopic(pubSubTopic).build();
Action action = Action.newBuilder().setPubSub(publishToPubSub).build();
// Configure the long running job we want the service to perform.
InspectJobConfig inspectJobConfig =
InspectJobConfig.newBuilder()
.setStorageConfig(storageConfig)
.setInspectConfig(inspectConfig)
.addActions(action)
.build();
// Create the request for the job configured above.
CreateDlpJobRequest createDlpJobRequest =
CreateDlpJobRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setInspectJob(inspectJobConfig)
.build();
// Use the client to send the request.
final DlpJob dlpJob = dlp.createDlpJob(createDlpJobRequest);
System.out.println("Job created: " + dlpJob.getName());
// Set up a Pub/Sub subscriber to listen on the job completion status
final SettableApiFuture<Boolean> done = SettableApiFuture.create();
ProjectSubscriptionName subscriptionName =
ProjectSubscriptionName.of(projectId, subscriptionId);
MessageReceiver messageHandler =
(PubsubMessage pubsubMessage, AckReplyConsumer ackReplyConsumer) -> {
handleMessage(dlpJob, done, pubsubMessage, ackReplyConsumer);
};
Subscriber subscriber = Subscriber.newBuilder(subscriptionName, messageHandler).build();
subscriber.startAsync();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try {
done.get(15, TimeUnit.MINUTES);
} catch (TimeoutException e) {
System.out.println("Job was not completed after 15 minutes.");
return;
} finally {
subscriber.stopAsync();
subscriber.awaitTerminated();
}
// Get the latest state of the job from the service
GetDlpJobRequest request = GetDlpJobRequest.newBuilder().setName(dlpJob.getName()).build();
DlpJob completedJob = dlp.getDlpJob(request);
// Parse the response and process results.
System.out.println("Job status: " + completedJob.getState());
System.out.println("Job name: " + dlpJob.getName());
InspectDataSourceDetails.Result result = completedJob.getInspectDetails().getResult();
System.out.println("Findings: ");
for (InfoTypeStats infoTypeStat : result.getInfoTypeStatsList()) {
System.out.print("\tInfo type: " + infoTypeStat.getInfoType().getName());
System.out.println("\tCount: " + infoTypeStat.getCount());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private static void handleMessage(
DlpJob job,
SettableApiFuture<Boolean> done,
PubsubMessage pubsubMessage,
AckReplyConsumer ackReplyConsumer) {
String messageAttribute = pubsubMessage.getAttributesMap().get("DlpJobName");
if (job.getName().equals(messageAttribute)) {
done.set(true);
ackReplyConsumer.ack();
} else {
ackReplyConsumer.nack();
}
}
}
// Import the Google Cloud client libraries
const DLP = require('@google-cloud/dlp');
const {PubSub} = require('@google-cloud/pubsub');
// Instantiates clients
const dlp = new DLP.DlpServiceClient();
const pubsub = new PubSub();
// The project ID to run the API call under
// const projectId = 'my-project';
// The name of the bucket where the file resides.
// const bucketName = 'YOUR-BUCKET';
// The path to the file within the bucket to inspect.
// Can contain wildcards, e.g. "my-image.*"
// const fileName = 'my-image.png';
// The minimum likelihood required before returning a match
// const minLikelihood = 'LIKELIHOOD_UNSPECIFIED';
// The maximum number of findings to report per request (0 = server maximum)
// const maxFindings = 0;
// The infoTypes of information to match
// const infoTypes = [{ name: 'PHONE_NUMBER' }, { name: 'EMAIL_ADDRESS' }, { name: 'CREDIT_CARD_NUMBER' }];
// The customInfoTypes of information to match
// const customInfoTypes = [{ infoType: { name: 'DICT_TYPE' }, dictionary: { wordList: { words: ['foo', 'bar', 'baz']}}},
// { infoType: { name: 'REGEX_TYPE' }, regex: {pattern: '\\(\\d{3}\\) \\d{3}-\\d{4}'}}];
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
async function inspectGCSFile() {
// Get reference to the file to be inspected
const storageItem = {
cloudStorageOptions: {
fileSet: {url: `gs://${bucketName}/${fileName}`},
},
};
// Construct request for creating an inspect job
const request = {
parent: `projects/${projectId}/locations/global`,
inspectJob: {
inspectConfig: {
infoTypes: infoTypes,
customInfoTypes: customInfoTypes,
minLikelihood: minLikelihood,
limits: {
maxFindingsPerRequest: maxFindings,
},
},
storageConfig: storageItem,
actions: [
{
pubSub: {
topic: `projects/${projectId}/topics/${topicId}`,
},
},
],
},
};
// Create a GCS File inspection job and wait for it to complete
const [topicResponse] = await pubsub.topic(topicId).get();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const subscription = await topicResponse.subscription(subscriptionId);
const [jobsResponse] = await dlp.createDlpJob(request);
// Get the job's ID
const jobName = jobsResponse.name;
// Watch the Pub/Sub topic until the DLP job finishes
await new Promise((resolve, reject) => {
const messageHandler = message => {
if (message.attributes && message.attributes.DlpJobName === jobName) {
message.ack();
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
resolve(jobName);
} else {
message.nack();
}
};
const errorHandler = err => {
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
reject(err);
};
subscription.on('message', messageHandler);
subscription.on('error', errorHandler);
});
setTimeout(() => {
console.log('Waiting for DLP job to fully complete');
}, 500);
const [job] = await dlp.getDlpJob({name: jobName});
console.log(`Job ${job.name} status: ${job.state}`);
const infoTypeStats = job.inspectDetails.result.infoTypeStats;
if (infoTypeStats.length > 0) {
infoTypeStats.forEach(infoTypeStat => {
console.log(
` Found ${infoTypeStat.count} instance(s) of infoType ${infoTypeStat.infoType.name}.`
);
});
} else {
console.log('No findings.');
}
}
await inspectGCSFile();
import threading
from typing import List, Optional
import google.cloud.dlp
import google.cloud.pubsub
def inspect_gcs_file(
project: str,
bucket: str,
filename: str,
topic_id: str,
subscription_id: str,
info_types: List[str],
custom_dictionaries: List[str] = None,
custom_regexes: List[str] = None,
min_likelihood: Optional[str] = None,
max_findings: Optional[int] = None,
timeout: int = 300,
) -> None:
"""Uses the Data Loss Prevention API to analyze a file on GCS.
Args:
project: The Google Cloud project id to use as a parent resource.
bucket: The name of the GCS bucket containing the file, as a string.
filename: The name of the file in the bucket, including the path, as a
string; e.g. 'images/myfile.png'.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
Returns:
None; the response from the API is printed to the terminal.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
if not info_types:
info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
info_types = [{"name": info_type} for info_type in info_types]
# Prepare custom_info_types by parsing the dictionary word lists and
# regex patterns.
if custom_dictionaries is None:
custom_dictionaries = []
dictionaries = [
{
"info_type": {"name": f"CUSTOM_DICTIONARY_{i}"},
"dictionary": {"word_list": {"words": custom_dict.split(",")}},
}
for i, custom_dict in enumerate(custom_dictionaries)
]
if custom_regexes is None:
custom_regexes = []
regexes = [
{
"info_type": {"name": f"CUSTOM_REGEX_{i}"},
"regex": {"pattern": custom_regex},
}
for i, custom_regex in enumerate(custom_regexes)
]
custom_info_types = dictionaries + regexes
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": info_types,
"custom_info_types": custom_info_types,
"min_likelihood": min_likelihood,
"limits": {"max_findings_per_request": max_findings},
}
# Construct a storage_config containing the file's URL.
url = f"gs://{bucket}/{filename}"
storage_config = {"cloud_storage_options": {"file_set": {"url": url}}}
# Convert the project id into full resource ids.
topic = google.cloud.pubsub.PublisherClient.topic_path(project, topic_id)
parent = f"projects/{project}/locations/global"
# Tell the API where to send a notification when the job is complete.
actions = [{"pub_sub": {"topic": topic}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job = {
"inspect_config": inspect_config,
"storage_config": storage_config,
"actions": actions,
}
operation = dlp.create_dlp_job(
request={"parent": parent, "inspect_job": inspect_job}
)
print(f"Inspection operation started: {operation.name}")
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber = google.cloud.pubsub.SubscriberClient()
subscription_path = subscriber.subscription_path(project, subscription_id)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done = threading.Event()
def callback(message: google.cloud.pubsub_v1.subscriber.message.Message) -> None:
try:
if message.attributes["DlpJobName"] == operation.name:
# This is the message we're looking for, so acknowledge it.
message.ack()
# Now that the job is done, fetch the results and print them.
job = dlp.get_dlp_job(request={"name": operation.name})
print(f"Job name: {job.name}")
if job.inspect_details.result.info_type_stats:
for finding in job.inspect_details.result.info_type_stats:
print(
f"Info type: {finding.info_type.name}; Count: {finding.count}"
)
else:
print("No findings.")
# Signal to the main thread that we can exit.
job_done.set()
else:
# This is not the message we're looking for.
message.drop()
except Exception as e:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print(e)
raise
subscriber.subscribe(subscription_path, callback=callback)
finished = job_done.wait(timeout=timeout)
if not finished:
print(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\CloudStorageOptions;
use Google\Cloud\Dlp\V2\CloudStorageOptions\FileSet;
use Google\Cloud\Dlp\V2\CreateDlpJobRequest;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\GetDlpJobRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect a file stored on Google Cloud Storage , using Pub/Sub for job status notifications.
*
* @param string $callingProjectId The project ID to run the API call under
* @param string $topicId The name of the Pub/Sub topic to notify once the job completes
* @param string $subscriptionId The name of the Pub/Sub subscription to use when listening for job
* @param string $bucketId The name of the bucket where the file resides
* @param string $file The path to the file within the bucket to inspect. Can contain wildcards e.g. "my-image.*"
* @param int $maxFindings (Optional) The maximum number of findings to report per request (0 = server maximum)
*/
function inspect_gcs(
string $callingProjectId,
string $topicId,
string $subscriptionId,
string $bucketId,
string $file,
int $maxFindings = 0
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// The infoTypes of information to match
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
$creditCardNumberInfoType = (new InfoType())
->setName('CREDIT_CARD_NUMBER');
$infoTypes = [$personNameInfoType, $creditCardNumberInfoType];
// The minimum likelihood required before returning a match
$minLikelihood = likelihood::LIKELIHOOD_UNSPECIFIED;
// Specify finding limits
$limits = (new FindingLimits())
->setMaxFindingsPerRequest($maxFindings);
// Construct items to be inspected
$fileSet = (new FileSet())
->setUrl('gs://' . $bucketId . '/' . $file);
$cloudStorageOptions = (new CloudStorageOptions())
->setFileSet($fileSet);
$storageConfig = (new StorageConfig())
->setCloudStorageOptions($cloudStorageOptions);
// Construct the inspect config object
$inspectConfig = (new InspectConfig())
->setMinLikelihood($minLikelihood)
->setLimits($limits)
->setInfoTypes($infoTypes);
// Construct the action to run when job completes
$pubSubAction = (new PublishToPubSub())
->setTopic($topic->name());
$action = (new Action())
->setPubSub($pubSubAction);
// Construct inspect job config to run
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request
$parent = "projects/$callingProjectId/locations/global";
$createDlpJobRequest = (new CreateDlpJobRequest())
->setParent($parent)
->setInspectJob($inspectJob);
$job = $dlp->createDlpJob($createDlpJobRequest);
// Poll Pub/Sub using exponential backoff until job finishes
// Consider using an asynchronous execution model such as Cloud Functions
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (
isset($message->attributes()['DlpJobName']) &&
$message->attributes()['DlpJobName'] === $job->getName()
) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$getDlpJobRequest = (new GetDlpJobRequest())
->setName($job->getName());
$job = $dlp->getDlpJob($getDlpJobRequest);
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while
}
}
print('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout
// Print finding counts
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
print('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(' Found %s instance(s) of infoType %s' . PHP_EOL, $infoTypeStat->getCount(), $infoTypeStat->getInfoType()->getName());
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
print('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
print('Unexpected job state. Most likely, the job is either running or has not yet started.');
}
}
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Cloud.PubSub.V1;
using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;
public class InspectGoogleCloudStorage
{
public static DlpJob InspectGCS(
string projectId,
Likelihood minLikelihood,
int maxFindings,
bool includeQuote,
IEnumerable<InfoType> infoTypes,
IEnumerable<CustomInfoType> customInfoTypes,
string bucketName,
string topicId,
string subscriptionId)
{
var inspectJob = new InspectJobConfig
{
StorageConfig = new StorageConfig
{
CloudStorageOptions = new CloudStorageOptions
{
FileSet = new CloudStorageOptions.Types.FileSet { Url = $"gs://{bucketName}/*.txt" },
BytesLimitPerFile = 1073741824
},
},
InspectConfig = new InspectConfig
{
InfoTypes = { infoTypes },
CustomInfoTypes = { customInfoTypes },
ExcludeInfoTypes = false,
IncludeQuote = includeQuote,
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
MinLikelihood = minLikelihood
},
Actions =
{
new Google.Cloud.Dlp.V2.Action
{
// Send results to Pub/Sub topic
PubSub = new Google.Cloud.Dlp.V2.Action.Types.PublishToPubSub
{
Topic = topicId,
}
}
}
};
// Issue Create Dlp Job Request
var client = DlpServiceClient.Create();
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
Parent = new LocationName(projectId, "global").ToString(),
};
// We need created job name
var dlpJob = client.CreateDlpJob(request);
// Get a pub/sub subscription and listen for DLP results
var fireEvent = new ManualResetEventSlim();
var subscriptionName = new SubscriptionName(projectId, subscriptionId);
var subscriber = SubscriberClient.CreateAsync(subscriptionName).Result;
subscriber.StartAsync(
(pubSubMessage, cancellationToken) =>
{
// Given a message that we receive on this subscription, we should either acknowledge or decline it
if (pubSubMessage.Attributes["DlpJobName"] == dlpJob.Name)
{
fireEvent.Set();
return Task.FromResult(SubscriberClient.Reply.Ack);
}
return Task.FromResult(SubscriberClient.Reply.Nack);
});
// We block here until receiving a signal from a separate thread that is waiting on a message indicating receiving a result of Dlp job
if (fireEvent.Wait(TimeSpan.FromMinutes(1)))
{
// Stop the thread that is listening to messages as a result of StartAsync call earlier
subscriber.StopAsync(CancellationToken.None).Wait();
// Now we can inspect full job results
var job = client.GetDlpJob(new GetDlpJobRequest { DlpJobName = new DlpJobName(projectId, dlpJob.Name) });
// Inspect Job details
Console.WriteLine($"Processed bytes: {job.InspectDetails.Result.ProcessedBytes}");
Console.WriteLine($"Total estimated bytes: {job.InspectDetails.Result.TotalEstimatedBytes}");
var stats = job.InspectDetails.Result.InfoTypeStats;
Console.WriteLine("Found stats:");
foreach (var stat in stats)
{
Console.WriteLine($"{stat.InfoType.Name}");
}
return job;
}
throw new InvalidOperationException("The wait failed on timeout");
}
}
Datastore 종류 검사
Google Cloud 콘솔을 사용하거나 Cloud DLP API에서 REST 또는 RPC 요청을 통해 또는 클라이언트 라이브러리를 사용하여 여러 언어의 프로그래매틱 방식으로 Datastore 종류의 검사를 설정할 수 있습니다.
민감한 정보 보호를 사용하여 Datastore 종류의 스캔 작업을 설정하려면 다음 안내를 따르세요.
콘솔
민감한 정보 보호를 사용하여 Datastore 종류의 스캔 작업을 설정하려면 다음 안내를 따르세요.
Google Cloud 콘솔의 민감한 정보 보호 섹션에서 작업 또는 작업 트리거 만들기 페이지로 이동합니다.
(선택사항) 4단계: 일정에서 시간 범위 지정 또는 주기적인 일정으로 작업을 실행하는 트리거 만들기를 선택하여 시간 범위 또는 일정을 구성합니다. 자세한 내용은 일정을 참조하세요.
만들기를 클릭합니다.
민감한 정보 보호 작업이 완료되면 작업 세부정보 페이지로 리디렉션되고 이메일로 알림을 받습니다. 작업 세부정보 페이지에서 검사 결과를 볼 수 있습니다.
(선택사항) 민감한 정보 보호 발견 항목을 BigQuery에 게시하도록 선택한 경우 작업 세부정보 페이지에서 BigQuery에서 발견 항목 보기를 클릭하여 BigQuery 웹 UI로 테이블을 엽니다. 그런 다음 테이블을 쿼리하고 발견 항목을 분석할 수 있습니다. BigQuery에서 결과를 쿼리하는 방법에 대한 자세한 내용은 BigQuery에서 민감한 정보 보호 발견 항목 쿼리를 참조하세요.
프로토콜
다음은 지정된 DLP API REST 엔드포인트를 대상으로 한 POST 요청으로 전송할 수 있는 샘플 JSON입니다. 이 JSON 예시는 DLP API를 사용하여 Datastore 종류를 검사하는 방법을 보여줍니다.
요청에 포함된 매개변수에 대한 자세한 내용은 이 주제 뒷부분의 '스토리지 검사 구성'을 참조하세요.
dlpJobs.create의 참조 페이지에서 API 탐색기로 이를 빠르게 시도해 볼 수 있습니다.
API 탐색기에서도 요청이 성공하면 새 스캔 작업이 생성됩니다. 스캔 작업을 제어하는 방법에 대한 자세한 내용은 이 주제 뒷부분의 검사 결과 가져오기를 참조하세요. JSON을 사용하여 DLP API로 요청을 전송하는 데 대한 일반적인 정보는 JSON 빠른 시작을 참조하세요.
import com.google.api.core.SettableApiFuture;
import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
import com.google.cloud.pubsub.v1.MessageReceiver;
import com.google.cloud.pubsub.v1.Subscriber;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DatastoreOptions;
import com.google.privacy.dlp.v2.DlpJob;
import com.google.privacy.dlp.v2.GetDlpJobRequest;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeStats;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectDataSourceDetails;
import com.google.privacy.dlp.v2.InspectJobConfig;
import com.google.privacy.dlp.v2.KindExpression;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PartitionId;
import com.google.privacy.dlp.v2.StorageConfig;
import com.google.pubsub.v1.ProjectSubscriptionName;
import com.google.pubsub.v1.PubsubMessage;
import java.io.IOException;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
import java.util.stream.Collectors;
import java.util.stream.Stream;
public class InspectDatastoreEntity {
public static void main(String[] args) throws Exception {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
String datastoreNamespace = "your-datastore-namespace";
String datastoreKind = "your-datastore-kind";
String topicId = "your-pubsub-topic-id";
String subscriptionId = "your-pubsub-subscription-id";
insepctDatastoreEntity(projectId, datastoreNamespace, datastoreKind, topicId, subscriptionId);
}
// Inspects a Datastore Entity.
public static void insepctDatastoreEntity(
String projectId,
String datastoreNamespce,
String datastoreKind,
String topicId,
String subscriptionId)
throws ExecutionException, InterruptedException, IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (DlpServiceClient dlp = DlpServiceClient.create()) {
// Specify the Datastore entity to be inspected.
PartitionId partitionId =
PartitionId.newBuilder()
.setProjectId(projectId)
.setNamespaceId(datastoreNamespce)
.build();
KindExpression kindExpression = KindExpression.newBuilder().setName(datastoreKind).build();
DatastoreOptions datastoreOptions =
DatastoreOptions.newBuilder().setKind(kindExpression).setPartitionId(partitionId).build();
StorageConfig storageConfig =
StorageConfig.newBuilder().setDatastoreOptions(datastoreOptions).build();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
List<InfoType> infoTypes =
Stream.of("PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD_NUMBER")
.map(it -> InfoType.newBuilder().setName(it).build())
.collect(Collectors.toList());
// Specify how the content should be inspected.
InspectConfig inspectConfig =
InspectConfig.newBuilder().addAllInfoTypes(infoTypes).setIncludeQuote(true).build();
// Specify the action that is triggered when the job completes.
String pubSubTopic = String.format("projects/%s/topics/%s", projectId, topicId);
Action.PublishToPubSub publishToPubSub =
Action.PublishToPubSub.newBuilder().setTopic(pubSubTopic).build();
Action action = Action.newBuilder().setPubSub(publishToPubSub).build();
// Configure the long running job we want the service to perform.
InspectJobConfig inspectJobConfig =
InspectJobConfig.newBuilder()
.setStorageConfig(storageConfig)
.setInspectConfig(inspectConfig)
.addActions(action)
.build();
// Create the request for the job configured above.
CreateDlpJobRequest createDlpJobRequest =
CreateDlpJobRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setInspectJob(inspectJobConfig)
.build();
// Use the client to send the request.
final DlpJob dlpJob = dlp.createDlpJob(createDlpJobRequest);
System.out.println("Job created: " + dlpJob.getName());
// Set up a Pub/Sub subscriber to listen on the job completion status
final SettableApiFuture<Boolean> done = SettableApiFuture.create();
ProjectSubscriptionName subscriptionName =
ProjectSubscriptionName.of(projectId, subscriptionId);
MessageReceiver messageHandler =
(PubsubMessage pubsubMessage, AckReplyConsumer ackReplyConsumer) -> {
handleMessage(dlpJob, done, pubsubMessage, ackReplyConsumer);
};
Subscriber subscriber = Subscriber.newBuilder(subscriptionName, messageHandler).build();
subscriber.startAsync();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try {
done.get(15, TimeUnit.MINUTES);
} catch (TimeoutException e) {
System.out.println("Job was not completed after 15 minutes.");
return;
} finally {
subscriber.stopAsync();
subscriber.awaitTerminated();
}
// Get the latest state of the job from the service
GetDlpJobRequest request = GetDlpJobRequest.newBuilder().setName(dlpJob.getName()).build();
DlpJob completedJob = dlp.getDlpJob(request);
// Parse the response and process results.
System.out.println("Job status: " + completedJob.getState());
System.out.println("Job name: " + dlpJob.getName());
InspectDataSourceDetails.Result result = completedJob.getInspectDetails().getResult();
System.out.println("Findings: ");
for (InfoTypeStats infoTypeStat : result.getInfoTypeStatsList()) {
System.out.print("\tInfo type: " + infoTypeStat.getInfoType().getName());
System.out.println("\tCount: " + infoTypeStat.getCount());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private static void handleMessage(
DlpJob job,
SettableApiFuture<Boolean> done,
PubsubMessage pubsubMessage,
AckReplyConsumer ackReplyConsumer) {
String messageAttribute = pubsubMessage.getAttributesMap().get("DlpJobName");
if (job.getName().equals(messageAttribute)) {
done.set(true);
ackReplyConsumer.ack();
} else {
ackReplyConsumer.nack();
}
}
}
// Import the Google Cloud client libraries
const DLP = require('@google-cloud/dlp');
const {PubSub} = require('@google-cloud/pubsub');
// Instantiates clients
const dlp = new DLP.DlpServiceClient();
const pubsub = new PubSub();
// The project ID to run the API call under
// const projectId = 'my-project';
// The project ID the target Datastore is stored under
// This may or may not equal the calling project ID
// const dataProjectId = 'my-project';
// (Optional) The ID namespace of the Datastore document to inspect.
// To ignore Datastore namespaces, set this to an empty string ('')
// const namespaceId = '';
// The kind of the Datastore entity to inspect.
// const kind = 'Person';
// The minimum likelihood required before returning a match
// const minLikelihood = 'LIKELIHOOD_UNSPECIFIED';
// The maximum number of findings to report per request (0 = server maximum)
// const maxFindings = 0;
// The infoTypes of information to match
// const infoTypes = [{ name: 'PHONE_NUMBER' }, { name: 'EMAIL_ADDRESS' }, { name: 'CREDIT_CARD_NUMBER' }];
// The customInfoTypes of information to match
// const customInfoTypes = [{ infoType: { name: 'DICT_TYPE' }, dictionary: { wordList: { words: ['foo', 'bar', 'baz']}}},
// { infoType: { name: 'REGEX_TYPE' }, regex: {pattern: '\\(\\d{3}\\) \\d{3}-\\d{4}'}}];
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
async function inspectDatastore() {
// Construct items to be inspected
const storageItems = {
datastoreOptions: {
partitionId: {
projectId: dataProjectId,
namespaceId: namespaceId,
},
kind: {
name: kind,
},
},
};
// Construct request for creating an inspect job
const request = {
parent: `projects/${projectId}/locations/global`,
inspectJob: {
inspectConfig: {
infoTypes: infoTypes,
customInfoTypes: customInfoTypes,
minLikelihood: minLikelihood,
limits: {
maxFindingsPerRequest: maxFindings,
},
},
storageConfig: storageItems,
actions: [
{
pubSub: {
topic: `projects/${projectId}/topics/${topicId}`,
},
},
],
},
};
// Run inspect-job creation request
const [topicResponse] = await pubsub.topic(topicId).get();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const subscription = await topicResponse.subscription(subscriptionId);
const [jobsResponse] = await dlp.createDlpJob(request);
const jobName = jobsResponse.name;
// Watch the Pub/Sub topic until the DLP job finishes
await new Promise((resolve, reject) => {
const messageHandler = message => {
if (message.attributes && message.attributes.DlpJobName === jobName) {
message.ack();
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
resolve(jobName);
} else {
message.nack();
}
};
const errorHandler = err => {
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
reject(err);
};
subscription.on('message', messageHandler);
subscription.on('error', errorHandler);
});
// Wait for DLP job to fully complete
setTimeout(() => {
console.log('Waiting for DLP job to fully complete');
}, 500);
const [job] = await dlp.getDlpJob({name: jobName});
console.log(`Job ${job.name} status: ${job.state}`);
const infoTypeStats = job.inspectDetails.result.infoTypeStats;
if (infoTypeStats.length > 0) {
infoTypeStats.forEach(infoTypeStat => {
console.log(
` Found ${infoTypeStat.count} instance(s) of infoType ${infoTypeStat.infoType.name}.`
);
});
} else {
console.log('No findings.');
}
}
await inspectDatastore();
import threading
from typing import List, Optional
import google.cloud.dlp
import google.cloud.pubsub
def inspect_datastore(
project: str,
datastore_project: str,
kind: str,
topic_id: str,
subscription_id: str,
info_types: List[str],
custom_dictionaries: List[str] = None,
custom_regexes: List[str] = None,
namespace_id: str = None,
min_likelihood: Optional[int] = None,
max_findings: Optional[int] = None,
timeout: int = 300,
) -> None:
"""Uses the Data Loss Prevention API to analyze Datastore data.
Args:
project: The Google Cloud project id to use as a parent resource.
datastore_project: The Google Cloud project id of the target Datastore.
kind: The kind of the Datastore entity to inspect, e.g. 'Person'.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
namespace_id: The namespace of the Datastore document, if applicable.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
Returns:
None; the response from the API is printed to the terminal.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
if not info_types:
info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
info_types = [{"name": info_type} for info_type in info_types]
# Prepare custom_info_types by parsing the dictionary word lists and
# regex patterns.
if custom_dictionaries is None:
custom_dictionaries = []
dictionaries = [
{
"info_type": {"name": f"CUSTOM_DICTIONARY_{i}"},
"dictionary": {"word_list": {"words": custom_dict.split(",")}},
}
for i, custom_dict in enumerate(custom_dictionaries)
]
if custom_regexes is None:
custom_regexes = []
regexes = [
{
"info_type": {"name": f"CUSTOM_REGEX_{i}"},
"regex": {"pattern": custom_regex},
}
for i, custom_regex in enumerate(custom_regexes)
]
custom_info_types = dictionaries + regexes
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": info_types,
"custom_info_types": custom_info_types,
"min_likelihood": min_likelihood,
"limits": {"max_findings_per_request": max_findings},
}
# Construct a storage_config containing the target Datastore info.
storage_config = {
"datastore_options": {
"partition_id": {
"project_id": datastore_project,
"namespace_id": namespace_id,
},
"kind": {"name": kind},
}
}
# Convert the project id into full resource ids.
topic = google.cloud.pubsub.PublisherClient.topic_path(project, topic_id)
parent = f"projects/{project}/locations/global"
# Tell the API where to send a notification when the job is complete.
actions = [{"pub_sub": {"topic": topic}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job = {
"inspect_config": inspect_config,
"storage_config": storage_config,
"actions": actions,
}
operation = dlp.create_dlp_job(
request={"parent": parent, "inspect_job": inspect_job}
)
print(f"Inspection operation started: {operation.name}")
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber = google.cloud.pubsub.SubscriberClient()
subscription_path = subscriber.subscription_path(project, subscription_id)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done = threading.Event()
def callback(message: google.cloud.pubsub_v1.subscriber.message.Message) -> None:
try:
if message.attributes["DlpJobName"] == operation.name:
# This is the message we're looking for, so acknowledge it.
message.ack()
# Now that the job is done, fetch the results and print them.
job = dlp.get_dlp_job(request={"name": operation.name})
print(f"Job name: {job.name}")
if job.inspect_details.result.info_type_stats:
for finding in job.inspect_details.result.info_type_stats:
print(
f"Info type: {finding.info_type.name}; Count: {finding.count}"
)
else:
print("No findings.")
# Signal to the main thread that we can exit.
job_done.set()
else:
# This is not the message we're looking for.
message.drop()
except Exception as e:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print(e)
raise
# Register the callback and wait on the event.
subscriber.subscribe(subscription_path, callback=callback)
finished = job_done.wait(timeout=timeout)
if not finished:
print(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\CreateDlpJobRequest;
use Google\Cloud\Dlp\V2\DatastoreOptions;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\GetDlpJobRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\KindExpression;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\PartitionId;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect Datastore, using Pub/Sub for job status notifications.
*
* @param string $callingProjectId The project ID to run the API call under
* @param string $dataProjectId The project ID containing the target Datastore
* @param string $topicId The name of the Pub/Sub topic to notify once the job completes
* @param string $subscriptionId The name of the Pub/Sub subscription to use when listening for job
* @param string $kind The datastore kind to inspect
* @param string $namespaceId The ID namespace of the Datastore document to inspect
* @param int $maxFindings (Optional) The maximum number of findings to report per request (0 = server maximum)
*/
function inspect_datastore(
string $callingProjectId,
string $dataProjectId,
string $topicId,
string $subscriptionId,
string $kind,
string $namespaceId,
int $maxFindings = 0
): void {
// Instantiate clients
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// The infoTypes of information to match
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
$phoneNumberInfoType = (new InfoType())
->setName('PHONE_NUMBER');
$infoTypes = [$personNameInfoType, $phoneNumberInfoType];
// The minimum likelihood required before returning a match
$minLikelihood = likelihood::LIKELIHOOD_UNSPECIFIED;
// Specify finding limits
$limits = (new FindingLimits())
->setMaxFindingsPerRequest($maxFindings);
// Construct items to be inspected
$partitionId = (new PartitionId())
->setProjectId($dataProjectId)
->setNamespaceId($namespaceId);
$kindExpression = (new KindExpression())
->setName($kind);
$datastoreOptions = (new DatastoreOptions())
->setPartitionId($partitionId)
->setKind($kindExpression);
// Construct the inspect config object
$inspectConfig = (new InspectConfig())
->setInfoTypes($infoTypes)
->setMinLikelihood($minLikelihood)
->setLimits($limits);
// Construct the storage config object
$storageConfig = (new StorageConfig())
->setDatastoreOptions($datastoreOptions);
// Construct the action to run when job completes
$pubSubAction = (new PublishToPubSub())
->setTopic($topic->name());
$action = (new Action())
->setPubSub($pubSubAction);
// Construct inspect job config to run
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request
$parent = "projects/$callingProjectId/locations/global";
$createDlpJobRequest = (new CreateDlpJobRequest())
->setParent($parent)
->setInspectJob($inspectJob);
$job = $dlp->createDlpJob($createDlpJobRequest);
// Poll Pub/Sub using exponential backoff until job finishes
// Consider using an asynchronous execution model such as Cloud Functions
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (
isset($message->attributes()['DlpJobName']) &&
$message->attributes()['DlpJobName'] === $job->getName()
) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$getDlpJobRequest = (new GetDlpJobRequest())
->setName($job->getName());
$job = $dlp->getDlpJob($getDlpJobRequest);
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while
}
}
print('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout
// Print finding counts
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
print('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(' Found %s instance(s) of infoType %s' . PHP_EOL, $infoTypeStat->getCount(), $infoTypeStat->getInfoType()->getName());
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
print('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
print('Unexpected job state.');
}
}
using Google.Api.Gax.ResourceNames;
using Google.Cloud.BigQuery.V2;
using Google.Cloud.Dlp.V2;
using Google.Protobuf.WellKnownTypes;
using System;
using System.Collections.Generic;
using System.Threading;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;
public class InspectCloudDataStore
{
public static object Inspect(
string projectId,
Likelihood minLikelihood,
int maxFindings,
bool includeQuote,
string kindName,
string namespaceId,
IEnumerable<InfoType> infoTypes,
IEnumerable<CustomInfoType> customInfoTypes,
string datasetId,
string tableId)
{
var inspectJob = new InspectJobConfig
{
StorageConfig = new StorageConfig
{
DatastoreOptions = new DatastoreOptions
{
Kind = new KindExpression { Name = kindName },
PartitionId = new PartitionId
{
NamespaceId = namespaceId,
ProjectId = projectId,
}
},
TimespanConfig = new StorageConfig.Types.TimespanConfig
{
StartTime = Timestamp.FromDateTime(System.DateTime.UtcNow.AddYears(-1)),
EndTime = Timestamp.FromDateTime(System.DateTime.UtcNow)
}
},
InspectConfig = new InspectConfig
{
InfoTypes = { infoTypes },
CustomInfoTypes = { customInfoTypes },
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
ExcludeInfoTypes = false,
IncludeQuote = includeQuote,
MinLikelihood = minLikelihood
},
Actions =
{
new Google.Cloud.Dlp.V2.Action
{
// Save results in BigQuery Table
SaveFindings = new Google.Cloud.Dlp.V2.Action.Types.SaveFindings
{
OutputConfig = new OutputStorageConfig
{
Table = new Google.Cloud.Dlp.V2.BigQueryTable
{
ProjectId = projectId,
DatasetId = datasetId,
TableId = tableId
}
}
},
}
}
};
// Issue Create Dlp Job Request
var client = DlpServiceClient.Create();
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
Parent = new LocationName(projectId, "global").ToString(),
};
// We need created job name
var dlpJob = client.CreateDlpJob(request);
var jobName = dlpJob.Name;
// Make sure the job finishes before inspecting the results.
// Alternatively, we can inspect results opportunistically, but
// for testing purposes, we want consistent outcome
var finishedJob = EnsureJobFinishes(projectId, jobName);
var bigQueryClient = BigQueryClient.Create(projectId);
var table = bigQueryClient.GetTable(datasetId, tableId);
// Return only first page of 10 rows
Console.WriteLine("DLP v2 Results:");
var firstPage = table.ListRows(new ListRowsOptions { StartIndex = 0, PageSize = 10 });
foreach (var item in firstPage)
{
Console.WriteLine($"\t {item[""]}");
}
return finishedJob;
}
private static DlpJob EnsureJobFinishes(string projectId, string jobName)
{
var client = DlpServiceClient.Create();
var request = new GetDlpJobRequest
{
DlpJobName = new DlpJobName(projectId, jobName),
};
// Simple logic that gives the job 5*30 sec at most to complete - for testing purposes only
var numOfAttempts = 5;
do
{
var dlpJob = client.GetDlpJob(request);
numOfAttempts--;
if (dlpJob.State != DlpJob.Types.JobState.Running)
{
return dlpJob;
}
Thread.Sleep(TimeSpan.FromSeconds(30));
} while (numOfAttempts > 0);
throw new InvalidOperationException("Job did not complete in time");
}
}
BigQuery 테이블 검사
REST 요청을 통해 민감한 정보 보호를 사용하거나 클라이언트 라이브러리를 사용하여 여러 언어의 프로그래매틱 방식으로 BigQuery 테이블 검사를 설정할 수 있습니다.
민감한 정보 보호를 사용하여 BigQuery 테이블의 스캔 작업을 설정하려면 다음 안내를 따르세요.
콘솔
민감한 정보 보호를 사용하여 BigQuery 테이블의 스캔 작업을 설정하려면 다음 안내를 따르세요.
Google Cloud 콘솔의 민감한 정보 보호 섹션에서 작업 또는 작업 트리거 만들기 페이지로 이동합니다.
Pub/Sub, Security Command Center, Data Catalog에 결과를 저장할 수도 있습니다. 자세한 내용은 액션 추가를 참조하세요.
(선택사항) 4단계: 일정에서 스캔을 한 번만 실행하려면 메뉴를 없음으로 설정합니다. 스캔이 주기적으로 실행되도록 예약하려면 주기적인 일정으로 작업을 실행하는 트리거 만들기를 클릭합니다. 자세한 내용은 일정을 참조하세요.
만들기를 클릭합니다.
민감한 정보 보호 작업이 완료되면 작업 세부정보 페이지로 리디렉션되고 이메일로 알림을 받습니다. 작업 세부정보 페이지에서 검사 결과를 볼 수 있습니다.
(선택사항) 민감한 정보 보호 발견 항목을 BigQuery에 게시하도록 선택한 경우 작업 세부정보 페이지에서 BigQuery에서 발견 항목 보기를 클릭하여 BigQuery 웹 UI로 테이블을 엽니다. 그런 다음 테이블을 쿼리하고 발견 항목을 분석할 수 있습니다. BigQuery에서 결과를 쿼리하는 방법에 대한 자세한 내용은 BigQuery에서 민감한 정보 보호 발견 항목 쿼리를 참조하세요.
프로토콜
다음은 지정된 DLP API REST 엔드포인트를 대상으로 한 POST 요청으로 전송할 수 있는 샘플 JSON입니다. 이 JSON 예는 DLP API를 사용하여 BigQuery 테이블을 검사하는 방법을 보여줍니다.
요청에 포함된 매개변수에 대한 자세한 내용은 이 주제 뒷부분의 '스토리지 검사 구성'을 참조하세요.
dlpJobs.create의 참조 페이지에서 API 탐색기로 이를 빠르게 시도해 볼 수 있습니다.
API 탐색기에서도 요청이 성공하면 새 스캔 작업이 생성됩니다. 스캔 작업을 제어하는 방법에 대한 자세한 내용은 이 주제 뒷부분의 '검사 결과 가져오기'를 참조하세요. JSON을 사용하여 DLP API로 요청을 전송하는 데 대한 일반적인 정보는 JSON 빠른 시작을 참조하세요.
import com.google.api.core.SettableApiFuture;
import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
import com.google.cloud.pubsub.v1.MessageReceiver;
import com.google.cloud.pubsub.v1.Subscriber;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.BigQueryOptions;
import com.google.privacy.dlp.v2.BigQueryTable;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DlpJob;
import com.google.privacy.dlp.v2.GetDlpJobRequest;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeStats;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectDataSourceDetails;
import com.google.privacy.dlp.v2.InspectJobConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.StorageConfig;
import com.google.pubsub.v1.ProjectSubscriptionName;
import com.google.pubsub.v1.PubsubMessage;
import java.io.IOException;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
import java.util.stream.Collectors;
import java.util.stream.Stream;
public class InspectBigQueryTable {
public static void main(String[] args) throws Exception {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
String bigQueryDatasetId = "your-bigquery-dataset-id";
String bigQueryTableId = "your-bigquery-table-id";
String topicId = "your-pubsub-topic-id";
String subscriptionId = "your-pubsub-subscription-id";
inspectBigQueryTable(projectId, bigQueryDatasetId, bigQueryTableId, topicId, subscriptionId);
}
// Inspects a BigQuery Table
public static void inspectBigQueryTable(
String projectId,
String bigQueryDatasetId,
String bigQueryTableId,
String topicId,
String subscriptionId)
throws ExecutionException, InterruptedException, IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (DlpServiceClient dlp = DlpServiceClient.create()) {
// Specify the BigQuery table to be inspected.
BigQueryTable tableReference =
BigQueryTable.newBuilder()
.setProjectId(projectId)
.setDatasetId(bigQueryDatasetId)
.setTableId(bigQueryTableId)
.build();
BigQueryOptions bigQueryOptions =
BigQueryOptions.newBuilder().setTableReference(tableReference).build();
StorageConfig storageConfig =
StorageConfig.newBuilder().setBigQueryOptions(bigQueryOptions).build();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
List<InfoType> infoTypes =
Stream.of("PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD_NUMBER")
.map(it -> InfoType.newBuilder().setName(it).build())
.collect(Collectors.toList());
// Specify how the content should be inspected.
InspectConfig inspectConfig =
InspectConfig.newBuilder().addAllInfoTypes(infoTypes).setIncludeQuote(true).build();
// Specify the action that is triggered when the job completes.
String pubSubTopic = String.format("projects/%s/topics/%s", projectId, topicId);
Action.PublishToPubSub publishToPubSub =
Action.PublishToPubSub.newBuilder().setTopic(pubSubTopic).build();
Action action = Action.newBuilder().setPubSub(publishToPubSub).build();
// Configure the long running job we want the service to perform.
InspectJobConfig inspectJobConfig =
InspectJobConfig.newBuilder()
.setStorageConfig(storageConfig)
.setInspectConfig(inspectConfig)
.addActions(action)
.build();
// Create the request for the job configured above.
CreateDlpJobRequest createDlpJobRequest =
CreateDlpJobRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setInspectJob(inspectJobConfig)
.build();
// Use the client to send the request.
final DlpJob dlpJob = dlp.createDlpJob(createDlpJobRequest);
System.out.println("Job created: " + dlpJob.getName());
// Set up a Pub/Sub subscriber to listen on the job completion status
final SettableApiFuture<Boolean> done = SettableApiFuture.create();
ProjectSubscriptionName subscriptionName =
ProjectSubscriptionName.of(projectId, subscriptionId);
MessageReceiver messageHandler =
(PubsubMessage pubsubMessage, AckReplyConsumer ackReplyConsumer) -> {
handleMessage(dlpJob, done, pubsubMessage, ackReplyConsumer);
};
Subscriber subscriber = Subscriber.newBuilder(subscriptionName, messageHandler).build();
subscriber.startAsync();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try {
done.get(15, TimeUnit.MINUTES);
} catch (TimeoutException e) {
System.out.println("Job was not completed after 15 minutes.");
return;
} finally {
subscriber.stopAsync();
subscriber.awaitTerminated();
}
// Get the latest state of the job from the service
GetDlpJobRequest request = GetDlpJobRequest.newBuilder().setName(dlpJob.getName()).build();
DlpJob completedJob = dlp.getDlpJob(request);
// Parse the response and process results.
System.out.println("Job status: " + completedJob.getState());
System.out.println("Job name: " + dlpJob.getName());
InspectDataSourceDetails.Result result = completedJob.getInspectDetails().getResult();
System.out.println("Findings: ");
for (InfoTypeStats infoTypeStat : result.getInfoTypeStatsList()) {
System.out.print("\tInfo type: " + infoTypeStat.getInfoType().getName());
System.out.println("\tCount: " + infoTypeStat.getCount());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private static void handleMessage(
DlpJob job,
SettableApiFuture<Boolean> done,
PubsubMessage pubsubMessage,
AckReplyConsumer ackReplyConsumer) {
String messageAttribute = pubsubMessage.getAttributesMap().get("DlpJobName");
if (job.getName().equals(messageAttribute)) {
done.set(true);
ackReplyConsumer.ack();
} else {
ackReplyConsumer.nack();
}
}
}
// Import the Google Cloud client libraries
const DLP = require('@google-cloud/dlp');
const {PubSub} = require('@google-cloud/pubsub');
// Instantiates clients
const dlp = new DLP.DlpServiceClient();
const pubsub = new PubSub();
// The project ID to run the API call under
// const projectId = 'my-project';
// The project ID the table is stored under
// This may or (for public datasets) may not equal the calling project ID
// const dataProjectId = 'my-project';
// The ID of the dataset to inspect, e.g. 'my_dataset'
// const datasetId = 'my_dataset';
// The ID of the table to inspect, e.g. 'my_table'
// const tableId = 'my_table';
// The minimum likelihood required before returning a match
// const minLikelihood = 'LIKELIHOOD_UNSPECIFIED';
// The maximum number of findings to report per request (0 = server maximum)
// const maxFindings = 0;
// The infoTypes of information to match
// const infoTypes = [{ name: 'PHONE_NUMBER' }, { name: 'EMAIL_ADDRESS' }, { name: 'CREDIT_CARD_NUMBER' }];
// The customInfoTypes of information to match
// const customInfoTypes = [{ infoType: { name: 'DICT_TYPE' }, dictionary: { wordList: { words: ['foo', 'bar', 'baz']}}},
// { infoType: { name: 'REGEX_TYPE' }, regex: {pattern: '\\(\\d{3}\\) \\d{3}-\\d{4}'}}];
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
async function inspectBigquery() {
// Construct item to be inspected
const storageItem = {
bigQueryOptions: {
tableReference: {
projectId: dataProjectId,
datasetId: datasetId,
tableId: tableId,
},
},
};
// Construct request for creating an inspect job
const request = {
parent: `projects/${projectId}/locations/global`,
inspectJob: {
inspectConfig: {
infoTypes: infoTypes,
customInfoTypes: customInfoTypes,
minLikelihood: minLikelihood,
limits: {
maxFindingsPerRequest: maxFindings,
},
},
storageConfig: storageItem,
actions: [
{
pubSub: {
topic: `projects/${projectId}/topics/${topicId}`,
},
},
],
},
};
// Run inspect-job creation request
const [topicResponse] = await pubsub.topic(topicId).get();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const subscription = await topicResponse.subscription(subscriptionId);
const [jobsResponse] = await dlp.createDlpJob(request);
const jobName = jobsResponse.name;
// Watch the Pub/Sub topic until the DLP job finishes
await new Promise((resolve, reject) => {
const messageHandler = message => {
if (message.attributes && message.attributes.DlpJobName === jobName) {
message.ack();
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
resolve(jobName);
} else {
message.nack();
}
};
const errorHandler = err => {
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
reject(err);
};
subscription.on('message', messageHandler);
subscription.on('error', errorHandler);
});
// Wait for DLP job to fully complete
setTimeout(() => {
console.log('Waiting for DLP job to fully complete');
}, 500);
const [job] = await dlp.getDlpJob({name: jobName});
console.log(`Job ${job.name} status: ${job.state}`);
const infoTypeStats = job.inspectDetails.result.infoTypeStats;
if (infoTypeStats.length > 0) {
infoTypeStats.forEach(infoTypeStat => {
console.log(
` Found ${infoTypeStat.count} instance(s) of infoType ${infoTypeStat.infoType.name}.`
);
});
} else {
console.log('No findings.');
}
}
await inspectBigquery();
import threading
from typing import List, Optional
import google.cloud.dlp
import google.cloud.pubsub
def inspect_bigquery(
project: str,
bigquery_project: str,
dataset_id: str,
table_id: str,
topic_id: str,
subscription_id: str,
info_types: List[str],
custom_dictionaries: List[str] = None,
custom_regexes: List[str] = None,
min_likelihood: Optional[int] = None,
max_findings: Optional[int] = None,
timeout: int = 500,
) -> None:
"""Uses the Data Loss Prevention API to analyze BigQuery data.
Args:
project: The Google Cloud project id to use as a parent resource.
bigquery_project: The Google Cloud project id of the target table.
dataset_id: The id of the target BigQuery dataset.
table_id: The id of the target BigQuery table.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
Returns:
None; the response from the API is printed to the terminal.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
if not info_types:
info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
info_types = [{"name": info_type} for info_type in info_types]
# Prepare custom_info_types by parsing the dictionary word lists and
# regex patterns.
if custom_dictionaries is None:
custom_dictionaries = []
dictionaries = [
{
"info_type": {"name": f"CUSTOM_DICTIONARY_{i}"},
"dictionary": {"word_list": {"words": custom_dict.split(",")}},
}
for i, custom_dict in enumerate(custom_dictionaries)
]
if custom_regexes is None:
custom_regexes = []
regexes = [
{
"info_type": {"name": f"CUSTOM_REGEX_{i}"},
"regex": {"pattern": custom_regex},
}
for i, custom_regex in enumerate(custom_regexes)
]
custom_info_types = dictionaries + regexes
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": info_types,
"custom_info_types": custom_info_types,
"min_likelihood": min_likelihood,
"limits": {"max_findings_per_request": max_findings},
}
# Construct a storage_config containing the target Bigquery info.
storage_config = {
"big_query_options": {
"table_reference": {
"project_id": bigquery_project,
"dataset_id": dataset_id,
"table_id": table_id,
}
}
}
# Convert the project id into full resource ids.
topic = google.cloud.pubsub.PublisherClient.topic_path(project, topic_id)
parent = f"projects/{project}/locations/global"
# Tell the API where to send a notification when the job is complete.
actions = [{"pub_sub": {"topic": topic}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job = {
"inspect_config": inspect_config,
"storage_config": storage_config,
"actions": actions,
}
operation = dlp.create_dlp_job(
request={"parent": parent, "inspect_job": inspect_job}
)
print(f"Inspection operation started: {operation.name}")
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber = google.cloud.pubsub.SubscriberClient()
subscription_path = subscriber.subscription_path(project, subscription_id)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done = threading.Event()
def callback(message: google.cloud.pubsub_v1.subscriber.message.Message) -> None:
try:
if message.attributes["DlpJobName"] == operation.name:
# This is the message we're looking for, so acknowledge it.
message.ack()
# Now that the job is done, fetch the results and print them.
job = dlp.get_dlp_job(request={"name": operation.name})
print(f"Job name: {job.name}")
if job.inspect_details.result.info_type_stats:
for finding in job.inspect_details.result.info_type_stats:
print(
"Info type: {}; Count: {}".format(
finding.info_type.name, finding.count
)
)
else:
print("No findings.")
# Signal to the main thread that we can exit.
job_done.set()
else:
# This is not the message we're looking for.
message.drop()
except Exception as e:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print(e)
raise
# Register the callback and wait on the event.
subscriber.subscribe(subscription_path, callback=callback)
finished = job_done.wait(timeout=timeout)
if not finished:
print(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\BigQueryOptions;
use Google\Cloud\Dlp\V2\BigQueryTable;
use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\CreateDlpJobRequest;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\GetDlpJobRequest;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect a BigQuery table , using Pub/Sub for job status notifications.
*
* @param string $callingProjectId The project ID to run the API call under
* @param string $dataProjectId The project ID containing the target Datastore
* @param string $topicId The name of the Pub/Sub topic to notify once the job completes
* @param string $subscriptionId The name of the Pub/Sub subscription to use when listening for job
* @param string $datasetId The ID of the dataset to inspect
* @param string $tableId The ID of the table to inspect
* @param int $maxFindings (Optional) The maximum number of findings to report per request (0 = server maximum)
*/
function inspect_bigquery(
string $callingProjectId,
string $dataProjectId,
string $topicId,
string $subscriptionId,
string $datasetId,
string $tableId,
int $maxFindings = 0
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// The infoTypes of information to match
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
$creditCardNumberInfoType = (new InfoType())
->setName('CREDIT_CARD_NUMBER');
$infoTypes = [$personNameInfoType, $creditCardNumberInfoType];
// The minimum likelihood required before returning a match
$minLikelihood = likelihood::LIKELIHOOD_UNSPECIFIED;
// Specify finding limits
$limits = (new FindingLimits())
->setMaxFindingsPerRequest($maxFindings);
// Construct items to be inspected
$bigqueryTable = (new BigQueryTable())
->setProjectId($dataProjectId)
->setDatasetId($datasetId)
->setTableId($tableId);
$bigQueryOptions = (new BigQueryOptions())
->setTableReference($bigqueryTable);
$storageConfig = (new StorageConfig())
->setBigQueryOptions($bigQueryOptions);
// Construct the inspect config object
$inspectConfig = (new InspectConfig())
->setMinLikelihood($minLikelihood)
->setLimits($limits)
->setInfoTypes($infoTypes);
// Construct the action to run when job completes
$pubSubAction = (new PublishToPubSub())
->setTopic($topic->name());
$action = (new Action())
->setPubSub($pubSubAction);
// Construct inspect job config to run
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request
$parent = "projects/$callingProjectId/locations/global";
$createDlpJobRequest = (new CreateDlpJobRequest())
->setParent($parent)
->setInspectJob($inspectJob);
$job = $dlp->createDlpJob($createDlpJobRequest);
// Poll Pub/Sub using exponential backoff until job finishes
// Consider using an asynchronous execution model such as Cloud Functions
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (isset($message->attributes()['DlpJobName']) &&
$message->attributes()['DlpJobName'] === $job->getName()) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$getDlpJobRequest = (new GetDlpJobRequest())
->setName($job->getName());
$job = $dlp->getDlpJob($getDlpJobRequest);
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while
}
}
print('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout
// Print finding counts
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
print('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(
' Found %s instance(s) of infoType %s' . PHP_EOL,
$infoTypeStat->getCount(),
$infoTypeStat->getInfoType()->getName()
);
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
print('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
print('Unexpected job state. Most likely, the job is either running or has not yet started.');
}
}
using Google.Api.Gax.ResourceNames;
using Google.Cloud.BigQuery.V2;
using Google.Cloud.Dlp.V2;
using Google.Protobuf.WellKnownTypes;
using System;
using System.Collections.Generic;
using System.Threading;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;
public class InspectBigQuery
{
public static object Inspect(
string projectId,
Likelihood minLikelihood,
int maxFindings,
bool includeQuote,
IEnumerable<FieldId> identifyingFields,
IEnumerable<InfoType> infoTypes,
IEnumerable<CustomInfoType> customInfoTypes,
string datasetId,
string tableId)
{
var inspectJob = new InspectJobConfig
{
StorageConfig = new StorageConfig
{
BigQueryOptions = new BigQueryOptions
{
TableReference = new Google.Cloud.Dlp.V2.BigQueryTable
{
ProjectId = projectId,
DatasetId = datasetId,
TableId = tableId,
},
IdentifyingFields =
{
identifyingFields
}
},
TimespanConfig = new StorageConfig.Types.TimespanConfig
{
StartTime = Timestamp.FromDateTime(System.DateTime.UtcNow.AddYears(-1)),
EndTime = Timestamp.FromDateTime(System.DateTime.UtcNow)
}
},
InspectConfig = new InspectConfig
{
InfoTypes = { infoTypes },
CustomInfoTypes = { customInfoTypes },
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
ExcludeInfoTypes = false,
IncludeQuote = includeQuote,
MinLikelihood = minLikelihood
},
Actions =
{
new Google.Cloud.Dlp.V2.Action
{
// Save results in BigQuery Table
SaveFindings = new Google.Cloud.Dlp.V2.Action.Types.SaveFindings
{
OutputConfig = new OutputStorageConfig
{
Table = new Google.Cloud.Dlp.V2.BigQueryTable
{
ProjectId = projectId,
DatasetId = datasetId,
TableId = tableId
}
}
},
}
}
};
// Issue Create Dlp Job Request
var client = DlpServiceClient.Create();
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
Parent = new LocationName(projectId, "global").ToString(),
};
// We need created job name
var dlpJob = client.CreateDlpJob(request);
var jobName = dlpJob.Name;
// Make sure the job finishes before inspecting the results.
// Alternatively, we can inspect results opportunistically, but
// for testing purposes, we want consistent outcome
var finishedJob = EnsureJobFinishes(projectId, jobName);
var bigQueryClient = BigQueryClient.Create(projectId);
var table = bigQueryClient.GetTable(datasetId, tableId);
// Return only first page of 10 rows
Console.WriteLine("DLP v2 Results:");
var firstPage = table.ListRows(new ListRowsOptions { StartIndex = 0, PageSize = 10 });
foreach (var item in firstPage)
{
Console.WriteLine($"\t {item[""]}");
}
return finishedJob;
}
private static DlpJob EnsureJobFinishes(string projectId, string jobName)
{
var client = DlpServiceClient.Create();
var request = new GetDlpJobRequest
{
DlpJobName = new DlpJobName(projectId, jobName),
};
// Simple logic that gives the job 5*30 sec at most to complete - for testing purposes only
var numOfAttempts = 5;
do
{
var dlpJob = client.GetDlpJob(request);
numOfAttempts--;
if (dlpJob.State != DlpJob.Types.JobState.Running)
{
return dlpJob;
}
Thread.Sleep(TimeSpan.FromSeconds(30));
} while (numOfAttempts > 0);
throw new InvalidOperationException("Job did not complete in time");
}
}
스토리지 검사 구성
Cloud Storage 위치, Datastore 종류 또는 BigQuery 테이블을 검사하려면 스캔할 데이터의 위치와 스캔할 데이터가 포함된 DLP API의 projects.dlpJobs.create 메서드로 요청을 전송합니다. 이러한 필수 매개변수 외에 스캔 결과를 쓸 위치, 크기 및 가능성 임계값 등도 지정할 수 있습니다. 요청이 성공하면 DlpJob 객체 인스턴스가 생성되며 이에 대해서는 '검사 결과 가져오기'에서 설명합니다.
inspectTemplateName 문자열: 선택사항. InspectConfig 객체의 기본값을 입력하는 데 사용되는 템플릿을 지정합니다.
이미 InspectConfig를 지정한 경우 템플릿 값이 병합됩니다.
Action 객체: 선택사항. 작업 완료 시 실행할 하나 이상의 액션. 각 액션은 나열된 순서에 따라 실행됩니다.
결과를 쓸 위치 또는 Pub/Sub 주제에 알림을 게시할지 여부를 여기에 지정합니다
jobId: (선택사항) 민감한 정보 보호에서 반환한 작업의 식별자입니다. jobId가 생략되거나 비어 있는 경우 시스템이 작업의 ID를 생성합니다. 지정되는 경우 작업에 이 ID 값이 할당됩니다.
작업 ID는 고유해야 하며 대문자와 소문자, 숫자, 하이픈을 포함할 수 있습니다. 즉, [a-zA-Z\\d-]+ 정규 표현식과 일치해야 합니다.
검사되는 콘텐츠의 양 제한
BigQuery 테이블 또는 Cloud Storage 버킷을 스캔하는 경우 민감한 정보 보호에 데이터 세트의 하위 집합을 스캔하는 방법이 포함됩니다. 이 기능은 전체 데이터 세트를 스캔하는 데 따르는 비용을 유발하지 않으면서 스캔 결과의 샘플링을 제공할 수 있습니다.
스캔되는 데이터의 양을 제한하여 Cloud Storage에서 샘플링을 사용하도록 설정할 수 있습니다. 입력 파일 집합에서 특정 크기 미만의 파일, 특정 파일 형식, 총 파일 수 대비 특정 비율만 스캔하도록 DLP API에 지시할 수 있습니다. 이렇게 하려면 CloudStorageOptions 내에 다음 선택사항 필드를 지정합니다.
bytesLimitPerFile: 파일에서 스캔할 최대 바이트 수를 설정합니다.
스캔되는 파일의 크기가 이 값보다 큰 경우 나머지 바이트는 생략됩니다. 이 필드를 설정해도 특정 파일 형식에는 영향을 주지 않습니다. 자세한 내용은 파일당 스캔하는 바이트 한도를 참조하세요.
fileTypes[]: 스캔에 포함할 FileTypes을 나열합니다. 다음 열거 유형 중 하나 이상으로 설정할 수 있습니다.
filesLimitPercent: 스캔할 파일 수를 입력 FileSet의 지정된 비율로 제한합니다.
여기서 0 또는 100을 지정하면 제한이 없음을 나타냅니다.
sampleMethod: 일부 바이트만 스캔하는 경우 바이트를 샘플링하는 방법. 이 값 지정은 bytesLimitPerFile과 함께 사용되는 경우에만 유효합니다. 지정되지 않으면 맨 위부터 스캔이 시작됩니다. 이 필드는 다음 두 값 중 하나로 설정할 수 있습니다.
TOP: 맨 위부터 스캔을 시작합니다.
RANDOM_START: bytesLimitPerFile에 지정된 크기보다 큰 각 파일에서 스캔을 시작할 오프셋을 무작위로 선택합니다. 스캔되는 바이트는 연속됩니다.
다음 예시는 DLP API를 사용하여 사용자 이름에 대한 Cloud Storage 버킷의 90% 하위 집합을 스캔하는 방법을 보여줍니다. 스캔은 데이터 세트에서 무작위 위치부터 시작되며 200바이트 미만의 텍스트 파일만 포함합니다.
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Cloud.PubSub.V1;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
public class InspectStorageWithSampling
{
public static async Task<DlpJob> InspectAsync(
string projectId,
string gcsUri,
string topicId,
string subId,
Likelihood minLikelihood = Likelihood.Possible,
IEnumerable<InfoType> infoTypes = null)
{
// Instantiate the dlp client.
var dlp = DlpServiceClient.Create();
// Construct Storage config by specifying the GCS file to be inspected
// and sample method.
var storageConfig = new StorageConfig
{
CloudStorageOptions = new CloudStorageOptions
{
FileSet = new CloudStorageOptions.Types.FileSet
{
Url = gcsUri
},
BytesLimitPerFile = 200,
FileTypes = { new FileType[] { FileType.Csv } },
FilesLimitPercent = 90,
SampleMethod = CloudStorageOptions.Types.SampleMethod.RandomStart
}
};
// Construct the Inspect Config and specify the type of info the inspection
// will look for.
var inspectConfig = new InspectConfig
{
InfoTypes =
{
infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } }
},
IncludeQuote = true,
MinLikelihood = minLikelihood
};
// Construct the pubsub action.
var actions = new Action[]
{
new Action
{
PubSub = new Action.Types.PublishToPubSub
{
Topic = $"projects/{projectId}/topics/{topicId}"
}
}
};
// Construct the inspect job config using above created objects.
var inspectJob = new InspectJobConfig
{
StorageConfig = storageConfig,
InspectConfig = inspectConfig,
Actions = { actions }
};
// Issue Create Dlp Job Request
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
ParentAsLocationName = new LocationName(projectId, "global"),
};
// We keep the name of the job that we just created.
var dlpJob = dlp.CreateDlpJob(request);
var jobName = dlpJob.Name;
// Listen to pub/sub for the job
var subscriptionName = new SubscriptionName(projectId, subId);
var subscriber = await SubscriberClient.CreateAsync(
subscriptionName);
await subscriber.StartAsync((PubsubMessage message, CancellationToken cancel) =>
{
if (message.Attributes["DlpJobName"] == jobName)
{
subscriber.StopAsync(cancel);
return Task.FromResult(SubscriberClient.Reply.Ack);
}
else
{
return Task.FromResult(SubscriberClient.Reply.Nack);
}
});
// Get the latest state of the job from the service
var resultJob = dlp.GetDlpJob(new GetDlpJobRequest
{
DlpJobName = DlpJobName.Parse(jobName)
});
// Parse the response and process results.
System.Console.WriteLine($"Job status: {resultJob.State}");
System.Console.WriteLine($"Job Name: {resultJob.Name}");
var result = resultJob.InspectDetails.Result;
foreach (var infoType in result.InfoTypeStats)
{
System.Console.WriteLine($"Info Type: {infoType.InfoType.Name}");
System.Console.WriteLine($"Count: {infoType.Count}");
}
return resultJob;
}
}
import (
"context"
"fmt"
"io"
"time"
dlp "cloud.google.com/go/dlp/apiv2"
"cloud.google.com/go/dlp/apiv2/dlppb"
"cloud.google.com/go/pubsub"
)
// inspectGcsFileWithSampling inspects a storage with sampling
func inspectGcsFileWithSampling(w io.Writer, projectID, gcsUri, topicID, subscriptionId string) error {
// projectId := "your-project-id"
// gcsUri := "gs://" + "your-bucket-name" + "/path/to/your/file.txt"
// topicID := "your-pubsub-topic-id"
// subscriptionId := "your-pubsub-subscription-id"
ctx := context.Background()
// Initialize a client once and reuse it to send multiple requests. Clients
// are safe to use across goroutines. When the client is no longer needed,
// call the Close method to cleanup its resources.
client, err := dlp.NewClient(ctx)
if err != nil {
return err
}
// Closing the client safely cleans up background resources.
defer client.Close()
// Specify the GCS file to be inspected and sampling configuration
var cloudStorageOptions = &dlppb.CloudStorageOptions{
FileSet: &dlppb.CloudStorageOptions_FileSet{
Url: gcsUri,
},
BytesLimitPerFile: int64(200),
FileTypes: []dlppb.FileType{
dlppb.FileType_TEXT_FILE,
},
FilesLimitPercent: int32(90),
SampleMethod: dlppb.CloudStorageOptions_RANDOM_START,
}
var storageConfig = &dlppb.StorageConfig{
Type: &dlppb.StorageConfig_CloudStorageOptions{
CloudStorageOptions: cloudStorageOptions,
},
}
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
// Specify how the content should be inspected.
var inspectConfig = &dlppb.InspectConfig{
InfoTypes: []*dlppb.InfoType{
{Name: "PERSON_NAME"},
},
ExcludeInfoTypes: true,
IncludeQuote: true,
MinLikelihood: dlppb.Likelihood_POSSIBLE,
}
// Create a PubSub Client used to listen for when the inspect job finishes.
pubsubClient, err := pubsub.NewClient(ctx, projectID)
if err != nil {
return err
}
defer pubsubClient.Close()
// Create a PubSub subscription we can use to listen for messages.
// Create the Topic if it doesn't exist.
t := pubsubClient.Topic(topicID)
if exists, err := t.Exists(ctx); err != nil {
return err
} else if !exists {
if t, err = pubsubClient.CreateTopic(ctx, topicID); err != nil {
return err
}
}
// Create the Subscription if it doesn't exist.
s := pubsubClient.Subscription(subscriptionId)
if exists, err := s.Exists(ctx); err != nil {
return err
} else if !exists {
if s, err = pubsubClient.CreateSubscription(ctx, subscriptionId, pubsub.SubscriptionConfig{Topic: t}); err != nil {
return err
}
}
// topic is the PubSub topic string where messages should be sent.
topic := "projects/" + projectID + "/topics/" + topicID
var action = &dlppb.Action{
Action: &dlppb.Action_PubSub{
PubSub: &dlppb.Action_PublishToPubSub{
Topic: topic,
},
},
}
// Configure the long running job we want the service to perform.
var inspectJobConfig = &dlppb.InspectJobConfig{
StorageConfig: storageConfig,
InspectConfig: inspectConfig,
Actions: []*dlppb.Action{
action,
},
}
// Create the request for the job configured above.
req := &dlppb.CreateDlpJobRequest{
Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
Job: &dlppb.CreateDlpJobRequest_InspectJob{
InspectJob: inspectJobConfig,
},
}
// Use the client to send the request.
j, err := client.CreateDlpJob(ctx, req)
if err != nil {
return err
}
fmt.Fprintf(w, "Job Created: %v", j.GetName())
// Wait for the inspect job to finish by waiting for a PubSub message.
// This only waits for 10 minutes. For long jobs, consider using a truly
// asynchronous execution model such as Cloud Functions.
ctx, cancel := context.WithTimeout(ctx, 10*time.Minute)
defer cancel()
err = s.Receive(ctx, func(ctx context.Context, msg *pubsub.Message) {
// If this is the wrong job, do not process the result.
if msg.Attributes["DlpJobName"] != j.GetName() {
msg.Nack()
return
}
msg.Ack()
// Stop listening for more messages.
defer cancel()
resp, err := client.GetDlpJob(ctx, &dlppb.GetDlpJobRequest{
Name: j.GetName(),
})
if err != nil {
fmt.Fprintf(w, "Error getting completed job: %v\n", err)
return
}
r := resp.GetInspectDetails().GetResult().GetInfoTypeStats()
if len(r) == 0 {
fmt.Fprintf(w, "No results")
return
}
for _, s := range r {
fmt.Fprintf(w, "\nFound %v instances of infoType %v\n", s.GetCount(), s.GetInfoType().GetName())
}
})
if err != nil {
return err
}
return nil
}
import com.google.api.core.SettableApiFuture;
import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
import com.google.cloud.pubsub.v1.MessageReceiver;
import com.google.cloud.pubsub.v1.Subscriber;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.CloudStorageOptions;
import com.google.privacy.dlp.v2.CloudStorageOptions.FileSet;
import com.google.privacy.dlp.v2.CloudStorageOptions.SampleMethod;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DlpJob;
import com.google.privacy.dlp.v2.FileType;
import com.google.privacy.dlp.v2.GetDlpJobRequest;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeStats;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectDataSourceDetails;
import com.google.privacy.dlp.v2.InspectJobConfig;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.StorageConfig;
import com.google.pubsub.v1.ProjectSubscriptionName;
import com.google.pubsub.v1.PubsubMessage;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
public class InspectGcsFileWithSampling {
public static void main(String[] args) throws Exception {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
String gcsUri = "gs://" + "your-bucket-name" + "/path/to/your/file.txt";
String topicId = "your-pubsub-topic-id";
String subscriptionId = "your-pubsub-subscription-id";
inspectGcsFileWithSampling(projectId, gcsUri, topicId, subscriptionId);
}
// Inspects a file in a Google Cloud Storage Bucket.
public static void inspectGcsFileWithSampling(
String projectId, String gcsUri, String topicId, String subscriptionId)
throws ExecutionException, InterruptedException, IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (DlpServiceClient dlp = DlpServiceClient.create()) {
// Specify the GCS file to be inspected and sampling configuration
CloudStorageOptions cloudStorageOptions =
CloudStorageOptions.newBuilder()
.setFileSet(FileSet.newBuilder().setUrl(gcsUri))
.setBytesLimitPerFile(200)
.addFileTypes(FileType.TEXT_FILE)
.setFilesLimitPercent(90)
.setSampleMethod(SampleMethod.RANDOM_START)
.build();
StorageConfig storageConfig =
StorageConfig.newBuilder().setCloudStorageOptions(cloudStorageOptions).build();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
// Specify how the content should be inspected.
InspectConfig inspectConfig =
InspectConfig.newBuilder()
.addInfoTypes(infoType)
.setExcludeInfoTypes(true)
.setIncludeQuote(true)
.setMinLikelihood(Likelihood.POSSIBLE)
.build();
// Specify the action that is triggered when the job completes.
String pubSubTopic = String.format("projects/%s/topics/%s", projectId, topicId);
Action.PublishToPubSub publishToPubSub =
Action.PublishToPubSub.newBuilder().setTopic(pubSubTopic).build();
Action action = Action.newBuilder().setPubSub(publishToPubSub).build();
// Configure the long running job we want the service to perform.
InspectJobConfig inspectJobConfig =
InspectJobConfig.newBuilder()
.setStorageConfig(storageConfig)
.setInspectConfig(inspectConfig)
.addActions(action)
.build();
// Create the request for the job configured above.
CreateDlpJobRequest createDlpJobRequest =
CreateDlpJobRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setInspectJob(inspectJobConfig)
.build();
// Use the client to send the request.
final DlpJob dlpJob = dlp.createDlpJob(createDlpJobRequest);
System.out.println("Job created: " + dlpJob.getName());
// Set up a Pub/Sub subscriber to listen on the job completion status
final SettableApiFuture<Boolean> done = SettableApiFuture.create();
ProjectSubscriptionName subscriptionName =
ProjectSubscriptionName.of(projectId, subscriptionId);
MessageReceiver messageHandler =
(PubsubMessage pubsubMessage, AckReplyConsumer ackReplyConsumer) -> {
handleMessage(dlpJob, done, pubsubMessage, ackReplyConsumer);
};
Subscriber subscriber = Subscriber.newBuilder(subscriptionName, messageHandler).build();
subscriber.startAsync();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try {
done.get(15, TimeUnit.MINUTES);
} catch (TimeoutException e) {
System.out.println("Job was not completed after 15 minutes.");
return;
} finally {
subscriber.stopAsync();
subscriber.awaitTerminated();
}
// Get the latest state of the job from the service
GetDlpJobRequest request = GetDlpJobRequest.newBuilder().setName(dlpJob.getName()).build();
DlpJob completedJob = dlp.getDlpJob(request);
// Parse the response and process results.
System.out.println("Job status: " + completedJob.getState());
System.out.println("Job name: " + dlpJob.getName());
InspectDataSourceDetails.Result result = completedJob.getInspectDetails().getResult();
System.out.println("Findings: ");
for (InfoTypeStats infoTypeStat : result.getInfoTypeStatsList()) {
System.out.print("\tInfo type: " + infoTypeStat.getInfoType().getName());
System.out.println("\tCount: " + infoTypeStat.getCount());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private static void handleMessage(
DlpJob job,
SettableApiFuture<Boolean> done,
PubsubMessage pubsubMessage,
AckReplyConsumer ackReplyConsumer) {
String messageAttribute = pubsubMessage.getAttributesMap().get("DlpJobName");
if (job.getName().equals(messageAttribute)) {
done.set(true);
ackReplyConsumer.ack();
} else {
ackReplyConsumer.nack();
}
}
}
// Import the Google Cloud client libraries
const DLP = require('@google-cloud/dlp');
const {PubSub} = require('@google-cloud/pubsub');
// Instantiates clients
const dlp = new DLP.DlpServiceClient();
const pubsub = new PubSub();
// The project ID to run the API call under
// const projectId = 'my-project';
// The gcs file path
// const gcsUri = 'gs://" + "your-bucket-name" + "/path/to/your/file.txt';
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
// const infoTypes = [{ name: 'PERSON_NAME' }];
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
// DLP Job max time (in milliseconds)
const DLP_JOB_WAIT_TIME = 15 * 1000 * 60;
async function inspectGcsFileSampling() {
// Specify the GCS file to be inspected and sampling configuration
const storageItemConfig = {
cloudStorageOptions: {
fileSet: {url: gcsUri},
bytesLimitPerFile: 200,
filesLimitPercent: 90,
fileTypes: [DLP.protos.google.privacy.dlp.v2.FileType.TEXT_FILE],
sampleMethod:
DLP.protos.google.privacy.dlp.v2.CloudStorageOptions.SampleMethod
.RANDOM_START,
},
};
// Specify how the content should be inspected.
const inspectConfig = {
infoTypes: infoTypes,
minLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.POSSIBLE,
includeQuote: true,
excludeInfoTypes: true,
};
// Specify the action that is triggered when the job completes.
const actions = [
{
pubSub: {
topic: `projects/${projectId}/topics/${topicId}`,
},
},
];
// Create the request for the job configured above.
const request = {
parent: `projects/${projectId}/locations/global`,
inspectJob: {
inspectConfig: inspectConfig,
storageConfig: storageItemConfig,
actions: actions,
},
};
// Use the client to send the request.
const [topicResponse] = await pubsub.topic(topicId).get();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const subscription = await topicResponse.subscription(subscriptionId);
const [jobsResponse] = await dlp.createDlpJob(request);
const jobName = jobsResponse.name;
// Watch the Pub/Sub topic until the DLP job finishes
await new Promise((resolve, reject) => {
// Set up the timeout
const timer = setTimeout(() => {
reject(new Error('Timeout'));
}, DLP_JOB_WAIT_TIME);
const messageHandler = message => {
if (message.attributes && message.attributes.DlpJobName === jobName) {
message.ack();
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
clearTimeout(timer);
resolve(jobName);
} else {
message.nack();
}
};
const errorHandler = err => {
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
clearTimeout(timer);
reject(err);
};
subscription.on('message', messageHandler);
subscription.on('error', errorHandler);
});
const [job] = await dlp.getDlpJob({name: jobName});
console.log(`Job ${job.name} status: ${job.state}`);
const infoTypeStats = job.inspectDetails.result.infoTypeStats;
if (infoTypeStats.length > 0) {
infoTypeStats.forEach(infoTypeStat => {
console.log(
` Found ${infoTypeStat.count} instance(s) of infoType ${infoTypeStat.infoType.name}.`
);
});
} else {
console.log('No findings.');
}
}
await inspectGcsFileSampling();
use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\BigQueryOptions\SampleMethod;
use Google\Cloud\Dlp\V2\CloudStorageOptions;
use Google\Cloud\Dlp\V2\CloudStorageOptions\FileSet;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect storage with sampling.
* The following examples demonstrate using the Cloud DLP API to scan a 90% subset of a
* Cloud Storage bucket for person names. The scan starts from a random location in the dataset
* and only includes text files under 200 bytes.
*
* @param string $callingProjectId The project ID to run the API call under.
* @param string $gcsUri Google Cloud Storage file url.
* @param string $topicId The ID of the Pub/Sub topic to notify once the job completes.
* @param string $subscriptionId The ID of the Pub/Sub subscription to use when listening for job.
*/
function inspect_gcs_with_sampling(
// TODO(developer): Replace sample parameters before running the code.
string $callingProjectId,
string $gcsUri = 'gs://GOOGLE_STORAGE_BUCKET_NAME/dlp_sample.csv',
string $topicId = 'dlp-pubsub-topic',
string $subscriptionId = 'dlp_subcription'
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// Construct the items to be inspected.
$cloudStorageOptions = (new CloudStorageOptions())
->setFileSet((new FileSet())
->setUrl($gcsUri))
->setBytesLimitPerFile(200)
->setFilesLimitPercent(90)
->setSampleMethod(SampleMethod::RANDOM_START);
$storageConfig = (new StorageConfig())
->setCloudStorageOptions($cloudStorageOptions);
// Specify the type of info the inspection will look for.
$phoneNumberInfoType = (new InfoType())
->setName('PHONE_NUMBER');
$emailAddressInfoType = (new InfoType())
->setName('EMAIL_ADDRESS');
$cardNumberInfoType = (new InfoType())
->setName('CREDIT_CARD_NUMBER');
$infoTypes = [$phoneNumberInfoType, $emailAddressInfoType, $cardNumberInfoType];
// Specify how the content should be inspected.
$inspectConfig = (new InspectConfig())
->setInfoTypes($infoTypes)
->setIncludeQuote(true);
// Construct the action to run when job completes.
$action = (new Action())
->setPubSub((new PublishToPubSub())
->setTopic($topic->name()));
// Construct inspect job config to run.
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request.
$parent = "projects/$callingProjectId/locations/global";
$job = $dlp->createDlpJob($parent, [
'inspectJob' => $inspectJob
]);
// Poll Pub/Sub using exponential backoff until job finishes.
// Consider using an asynchronous execution model such as Cloud Functions.
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (
isset($message->attributes()['DlpJobName']) &&
$message->attributes()['DlpJobName'] === $job->getName()
) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$job = $dlp->getDlpJob($job->getName());
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while.
}
}
printf('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds.
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout.
// Print finding counts.
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
printf('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(
' Found %s instance(s) of infoType %s' . PHP_EOL,
$infoTypeStat->getCount(),
$infoTypeStat->getInfoType()->getName()
);
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
printf('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
printf('Unexpected job state. Most likely, the job is either running or has not yet started.');
}
}
import threading
from typing import List
import google.cloud.dlp
import google.cloud.pubsub
def inspect_gcs_with_sampling(
project: str,
bucket: str,
topic_id: str,
subscription_id: str,
info_types: List[str] = None,
file_types: List[str] = None,
min_likelihood: str = None,
max_findings: int = None,
timeout: int = 300,
) -> None:
"""Uses the Data Loss Prevention API to analyze files in GCS by
limiting the amount of data to be scanned.
Args:
project: The Google Cloud project id to use as a parent resource.
bucket: The name of the GCS bucket containing the file, as a string.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
info_types: A list of strings representing infoTypes to look for.
A full list of info type categories can be fetched from the API.
file_types: Type of files in gcs bucket where the inspection would happen.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries.
if not info_types:
info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
info_types = [{"name": info_type} for info_type in info_types]
# Specify how the content should be inspected. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": info_types,
"exclude_info_types": True,
"include_quote": True,
"min_likelihood": min_likelihood,
"limits": {"max_findings_per_request": max_findings},
}
# Setting default file types as CSV files
if not file_types:
file_types = ["CSV"]
# Construct a cloud_storage_options dictionary with the bucket's URL.
url = f"gs://{bucket}/*"
storage_config = {
"cloud_storage_options": {
"file_set": {"url": url},
"bytes_limit_per_file": 200,
"file_types": file_types,
"files_limit_percent": 90,
"sample_method": "RANDOM_START",
}
}
# Tell the API where to send a notification when the job is complete.
topic = google.cloud.pubsub.PublisherClient.topic_path(project, topic_id)
actions = [{"pub_sub": {"topic": topic}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job = {
"inspect_config": inspect_config,
"storage_config": storage_config,
"actions": actions,
}
# Convert the project id into full resource ids.
parent = f"projects/{project}/locations/global"
# Call the API
operation = dlp.create_dlp_job(
request={"parent": parent, "inspect_job": inspect_job}
)
print(f"Inspection operation started: {operation.name}")
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber = google.cloud.pubsub.SubscriberClient()
subscription_path = subscriber.subscription_path(project, subscription_id)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done = threading.Event()
def callback(message):
try:
if message.attributes["DlpJobName"] == operation.name:
# This is the message we're looking for, so acknowledge it.
message.ack()
# Now that the job is done, fetch the results and print them.
job = dlp.get_dlp_job(request={"name": operation.name})
print(f"Job name: {job.name}")
if job.inspect_details.result.info_type_stats:
print("Findings:")
for finding in job.inspect_details.result.info_type_stats:
print(
f"Info type: {finding.info_type.name}; Count: {finding.count}"
)
else:
print("No findings.")
# Signal to the main thread that we can exit.
job_done.set()
else:
# This is not the message we're looking for.
message.drop()
except Exception as e:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print(e)
raise
# Register the callback and wait on the event.
subscriber.subscribe(subscription_path, callback=callback)
finished = job_done.wait(timeout=timeout)
if not finished:
print(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
스캔되는 데이터의 양을 제한하여 BigQuery에서 샘플링을 사용 설정하려면 BigQueryOptions 내에 다음 옵션 필드를 지정하세요.
rowsLimit: 스캔할 최대 행 수입니다. 테이블에 이 값보다 더 많은 행이 있는 경우 나머지 행은 생략됩니다. 설정하지 않거나 0으로 설정하면 모든 행이 스캔됩니다.
rowsLimitPercent: 스캔할 행의 최대 비율입니다(0~100). 나머지 행은 생략됩니다. 이 값을 0 또는 100으로 설정하면 제한이 없습니다. 기본값은 0입니다. rowsLimit 및 rowsLimitPercent 중 하나만 지정할 수 있습니다.
sampleMethod: 모든 행이 스캔되지 않는 경우 행을 샘플링하는 방법. 지정되지 않으면 맨 위부터 스캔이 시작됩니다. 이 필드는 다음 두 값 중 하나로 설정할 수 있습니다.
TOP: 맨 위부터 스캔을 시작합니다.
RANDOM_START: 무작위로 선택한 행부터 스캔을 시작합니다.
excludedFields: 읽지 않을 열을 고유하게 식별하는 테이블 필드입니다. 이렇게 하면 스캔되는 데이터의 양을 줄이고 검사 작업의 전체 비용을 줄일 수 있습니다.
includedFields: 스캔할 테이블 내의 특정 행을 고유하게 식별하는 테이블 필드입니다.
특히 파티션을 나눈 테이블을 스캔할 때 스캔되는 데이터를 제한하는 데 유용한 또 다른 기능은 TimespanConfig입니다.
TimespanConfig를 사용하면 시작 및 종료 시간 값을 제공하여 BigQuery 테이블 행을 필터링하여 기간을 정의할 수 있습니다. 그러면 민감한 정보 보호가 해당 기간 내에 타임스탬프가 포함된 행만 스캔합니다.
다음 예시에서는 DLP API를 사용하여 BigQuery 테이블의 1000행 하위 집합을 스캔하는 방법을 보여줍니다. 스캔은 무작위 행부터 시작됩니다.
import (
"context"
"fmt"
"io"
"time"
dlp "cloud.google.com/go/dlp/apiv2"
"cloud.google.com/go/dlp/apiv2/dlppb"
"cloud.google.com/go/pubsub"
)
// inspectBigQueryTableWithSampling inspect bigQueries for sensitive data with sampling
func inspectBigQueryTableWithSampling(w io.Writer, projectID, topicID, subscriptionID string) error {
// projectId := "your-project-id"
// topicID := "your-pubsub-topic-id"
// or provide a topicID name to create one
// subscriptionID := "your-pubsub-subscription-id"
// or provide a subscription name to create one
ctx := context.Background()
// Initialize a client once and reuse it to send multiple requests. Clients
// are safe to use across goroutines. When the client is no longer needed,
// call the Close method to cleanup its resources.
client, err := dlp.NewClient(ctx)
if err != nil {
return err
}
// Closing the client safely cleans up background resources.
defer client.Close()
// Specify the BigQuery table to be inspected.
tableReference := &dlppb.BigQueryTable{
ProjectId: "bigquery-public-data",
DatasetId: "usa_names",
TableId: "usa_1910_current",
}
bigQueryOptions := &dlppb.BigQueryOptions{
TableReference: tableReference,
RowsLimit: int64(10000),
SampleMethod: dlppb.BigQueryOptions_RANDOM_START,
IdentifyingFields: []*dlppb.FieldId{
{Name: "name"},
},
}
// Provide storage config with BigqueryOptions
storageConfig := &dlppb.StorageConfig{
Type: &dlppb.StorageConfig_BigQueryOptions{
BigQueryOptions: bigQueryOptions,
},
}
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
infoTypes := []*dlppb.InfoType{
{Name: "PERSON_NAME"},
}
// Specify how the content should be inspected.
inspectConfig := &dlppb.InspectConfig{
InfoTypes: infoTypes,
IncludeQuote: true,
}
// Create a PubSub Client used to listen for when the inspect job finishes.
pubsubClient, err := pubsub.NewClient(ctx, projectID)
if err != nil {
return err
}
defer pubsubClient.Close()
// Create a PubSub subscription we can use to listen for messages.
// Create the Topic if it doesn't exist.
t := pubsubClient.Topic(topicID)
if exists, err := t.Exists(ctx); err != nil {
return err
} else if !exists {
if t, err = pubsubClient.CreateTopic(ctx, topicID); err != nil {
return err
}
}
// Create the Subscription if it doesn't exist.
s := pubsubClient.Subscription(subscriptionID)
if exists, err := s.Exists(ctx); err != nil {
return err
} else if !exists {
if s, err = pubsubClient.CreateSubscription(ctx, subscriptionID, pubsub.SubscriptionConfig{Topic: t}); err != nil {
return err
}
}
// topic is the PubSub topic string where messages should be sent.
topic := fmt.Sprintf("projects/%s/topics/%s", projectID, topicID)
action := &dlppb.Action{
Action: &dlppb.Action_PubSub{
PubSub: &dlppb.Action_PublishToPubSub{
Topic: topic,
},
},
}
// Configure the long running job we want the service to perform.
inspectJobConfig := &dlppb.InspectJobConfig{
StorageConfig: storageConfig,
InspectConfig: inspectConfig,
Actions: []*dlppb.Action{
action,
},
}
// Create the request for the job configured above.
req := &dlppb.CreateDlpJobRequest{
Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
Job: &dlppb.CreateDlpJobRequest_InspectJob{
InspectJob: inspectJobConfig,
},
}
// Use the client to send the request.
j, err := client.CreateDlpJob(ctx, req)
if err != nil {
return err
}
fmt.Fprintf(w, "Job Created: %v", j.GetName())
// Wait for the inspect job to finish by waiting for a PubSub message.
// This only waits for 10 minutes. For long jobs, consider using a truly
// asynchronous execution model such as Cloud Functions.
c, cancel := context.WithTimeout(ctx, 10*time.Minute)
defer cancel()
err = s.Receive(c, func(ctx context.Context, msg *pubsub.Message) {
// If this is the wrong job, do not process the result.
if msg.Attributes["DlpJobName"] != j.GetName() {
msg.Nack()
return
}
msg.Ack()
// Stop listening for more messages.
defer cancel()
})
if err != nil {
return err
}
resp, err := client.GetDlpJob(ctx, &dlppb.GetDlpJobRequest{
Name: j.GetName(),
})
if err != nil {
return err
}
r := resp.GetInspectDetails().GetResult().GetInfoTypeStats()
if len(r) == 0 {
fmt.Fprintf(w, "No results")
return err
}
for _, s := range r {
fmt.Fprintf(w, "\nFound %v instances of infoType %v\n", s.GetCount(), s.GetInfoType().GetName())
}
return nil
}
import com.google.api.core.SettableApiFuture;
import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.cloud.pubsub.v1.AckReplyConsumer;
import com.google.cloud.pubsub.v1.MessageReceiver;
import com.google.cloud.pubsub.v1.Subscriber;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.BigQueryOptions;
import com.google.privacy.dlp.v2.BigQueryOptions.SampleMethod;
import com.google.privacy.dlp.v2.BigQueryTable;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DlpJob;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.GetDlpJobRequest;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeStats;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectDataSourceDetails;
import com.google.privacy.dlp.v2.InspectJobConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.StorageConfig;
import com.google.pubsub.v1.ProjectSubscriptionName;
import com.google.pubsub.v1.PubsubMessage;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;
public class InspectBigQueryTableWithSampling {
public static void main(String[] args) throws Exception {
// TODO(developer): Replace these variables before running the sample.
String projectId = "your-project-id";
String topicId = "your-pubsub-topic-id";
String subscriptionId = "your-pubsub-subscription-id";
inspectBigQueryTableWithSampling(projectId, topicId, subscriptionId);
}
// Inspects a BigQuery Table
public static void inspectBigQueryTableWithSampling(
String projectId, String topicId, String subscriptionId)
throws ExecutionException, InterruptedException, IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (DlpServiceClient dlp = DlpServiceClient.create()) {
// Specify the BigQuery table to be inspected.
BigQueryTable tableReference =
BigQueryTable.newBuilder()
.setProjectId("bigquery-public-data")
.setDatasetId("usa_names")
.setTableId("usa_1910_current")
.build();
BigQueryOptions bigQueryOptions =
BigQueryOptions.newBuilder()
.setTableReference(tableReference)
.setRowsLimit(1000)
.setSampleMethod(SampleMethod.RANDOM_START)
.addIdentifyingFields(FieldId.newBuilder().setName("name"))
.build();
StorageConfig storageConfig =
StorageConfig.newBuilder().setBigQueryOptions(bigQueryOptions).build();
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
// Specify how the content should be inspected.
InspectConfig inspectConfig =
InspectConfig.newBuilder().addInfoTypes(infoType).setIncludeQuote(true).build();
// Specify the action that is triggered when the job completes.
String pubSubTopic = String.format("projects/%s/topics/%s", projectId, topicId);
Action.PublishToPubSub publishToPubSub =
Action.PublishToPubSub.newBuilder().setTopic(pubSubTopic).build();
Action action = Action.newBuilder().setPubSub(publishToPubSub).build();
// Configure the long running job we want the service to perform.
InspectJobConfig inspectJobConfig =
InspectJobConfig.newBuilder()
.setStorageConfig(storageConfig)
.setInspectConfig(inspectConfig)
.addActions(action)
.build();
// Create the request for the job configured above.
CreateDlpJobRequest createDlpJobRequest =
CreateDlpJobRequest.newBuilder()
.setParent(LocationName.of(projectId, "global").toString())
.setInspectJob(inspectJobConfig)
.build();
// Use the client to send the request.
final DlpJob dlpJob = dlp.createDlpJob(createDlpJobRequest);
System.out.println("Job created: " + dlpJob.getName());
// Set up a Pub/Sub subscriber to listen on the job completion status
final SettableApiFuture<Boolean> done = SettableApiFuture.create();
ProjectSubscriptionName subscriptionName =
ProjectSubscriptionName.of(projectId, subscriptionId);
MessageReceiver messageHandler =
(PubsubMessage pubsubMessage, AckReplyConsumer ackReplyConsumer) -> {
handleMessage(dlpJob, done, pubsubMessage, ackReplyConsumer);
};
Subscriber subscriber = Subscriber.newBuilder(subscriptionName, messageHandler).build();
subscriber.startAsync();
// Wait for job completion semi-synchronously
// For long jobs, consider using a truly asynchronous execution model such as Cloud Functions
try {
done.get(15, TimeUnit.MINUTES);
} catch (TimeoutException e) {
System.out.println("Job was not completed after 15 minutes.");
return;
} finally {
subscriber.stopAsync();
subscriber.awaitTerminated();
}
// Get the latest state of the job from the service
GetDlpJobRequest request = GetDlpJobRequest.newBuilder().setName(dlpJob.getName()).build();
DlpJob completedJob = dlp.getDlpJob(request);
// Parse the response and process results.
System.out.println("Job status: " + completedJob.getState());
System.out.println("Job name: " + dlpJob.getName());
InspectDataSourceDetails.Result result = completedJob.getInspectDetails().getResult();
System.out.println("Findings: ");
for (InfoTypeStats infoTypeStat : result.getInfoTypeStatsList()) {
System.out.print("\tInfo type: " + infoTypeStat.getInfoType().getName());
System.out.println("\tCount: " + infoTypeStat.getCount());
}
}
}
// handleMessage injects the job and settableFuture into the message reciever interface
private static void handleMessage(
DlpJob job,
SettableApiFuture<Boolean> done,
PubsubMessage pubsubMessage,
AckReplyConsumer ackReplyConsumer) {
String messageAttribute = pubsubMessage.getAttributesMap().get("DlpJobName");
if (job.getName().equals(messageAttribute)) {
done.set(true);
ackReplyConsumer.ack();
} else {
ackReplyConsumer.nack();
}
}
}
// Import the Google Cloud client libraries
const DLP = require('@google-cloud/dlp');
const {PubSub} = require('@google-cloud/pubsub');
// Instantiates clients
const dlp = new DLP.DlpServiceClient();
const pubsub = new PubSub();
// The project ID to run the API call under
// const projectId = 'my-project';
// The project ID the table is stored under
// This may or (for public datasets) may not equal the calling project ID
// const dataProjectId = 'my-project';
// The ID of the dataset to inspect, e.g. 'my_dataset'
// const datasetId = 'my_dataset';
// The ID of the table to inspect, e.g. 'my_table'
// const tableId = 'my_table';
// The name of the Pub/Sub topic to notify once the job completes
// TODO(developer): create a Pub/Sub topic to use for this
// const topicId = 'MY-PUBSUB-TOPIC'
// The name of the Pub/Sub subscription to use when listening for job
// completion notifications
// TODO(developer): create a Pub/Sub subscription to use for this
// const subscriptionId = 'MY-PUBSUB-SUBSCRIPTION'
// DLP Job max time (in milliseconds)
const DLP_JOB_WAIT_TIME = 15 * 1000 * 60;
async function inspectBigqueryWithSampling() {
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
const infoTypes = [{name: 'PERSON_NAME'}];
// Specify the BigQuery options required for inspection.
const storageItem = {
bigQueryOptions: {
tableReference: {
projectId: dataProjectId,
datasetId: datasetId,
tableId: tableId,
},
rowsLimit: 1000,
sampleMethod:
DLP.protos.google.privacy.dlp.v2.BigQueryOptions.SampleMethod
.RANDOM_START,
includedFields: [{name: 'name'}],
},
};
// Specify the action that is triggered when the job completes.
const actions = [
{
pubSub: {
topic: `projects/${projectId}/topics/${topicId}`,
},
},
];
// Construct request for creating an inspect job
const request = {
parent: `projects/${projectId}/locations/global`,
inspectJob: {
inspectConfig: {
infoTypes: infoTypes,
includeQuote: true,
},
storageConfig: storageItem,
actions: actions,
},
};
// Use the client to send the request.
const [topicResponse] = await pubsub.topic(topicId).get();
// Verify the Pub/Sub topic and listen for job notifications via an
// existing subscription.
const subscription = await topicResponse.subscription(subscriptionId);
const [jobsResponse] = await dlp.createDlpJob(request);
const jobName = jobsResponse.name;
// Watch the Pub/Sub topic until the DLP job finishes
await new Promise((resolve, reject) => {
// Set up the timeout
const timer = setTimeout(() => {
reject(new Error('Timeout'));
}, DLP_JOB_WAIT_TIME);
const messageHandler = message => {
if (message.attributes && message.attributes.DlpJobName === jobName) {
message.ack();
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
clearTimeout(timer);
resolve(jobName);
} else {
message.nack();
}
};
const errorHandler = err => {
subscription.removeListener('message', messageHandler);
subscription.removeListener('error', errorHandler);
clearTimeout(timer);
reject(err);
};
subscription.on('message', messageHandler);
subscription.on('error', errorHandler);
});
const [job] = await dlp.getDlpJob({name: jobName});
console.log(`Job ${job.name} status: ${job.state}`);
const infoTypeStats = job.inspectDetails.result.infoTypeStats;
if (infoTypeStats.length > 0) {
infoTypeStats.forEach(infoTypeStat => {
console.log(
` Found ${infoTypeStat.count} instance(s) of infoType ${infoTypeStat.infoType.name}.`
);
});
} else {
console.log('No findings.');
}
}
await inspectBigqueryWithSampling();
use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\BigQueryOptions;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\Dlp\V2\BigQueryTable;
use Google\Cloud\Dlp\V2\DlpJob\JobState;
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishToPubSub;
use Google\Cloud\Dlp\V2\BigQueryOptions\SampleMethod;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\PubSub\PubSubClient;
/**
* Inspect BigQuery for sensitive data with sampling.
* The following examples demonstrate using the Cloud Data Loss Prevention
* API to scan a 1000-row subset of a BigQuery table. The scan starts from
* a random row.
*
* @param string $callingProjectId The project ID to run the API call under.
* @param string $topicId The Pub/Sub topic ID to notify once the job is completed.
* @param string $subscriptionId The Pub/Sub subscription ID to use when listening for job.
* @param string $projectId The Google Cloud Project ID.
* @param string $datasetId The BigQuery Dataset ID.
* @param string $tableId The BigQuery Table ID to be inspected.
*/
function inspect_bigquery_with_sampling(
string $callingProjectId,
string $topicId,
string $subscriptionId,
string $projectId,
string $datasetId,
string $tableId
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
$pubsub = new PubSubClient();
$topic = $pubsub->topic($topicId);
// Specify the BigQuery table to be inspected.
$bigqueryTable = (new BigQueryTable())
->setProjectId($projectId)
->setDatasetId($datasetId)
->setTableId($tableId);
$bigQueryOptions = (new BigQueryOptions())
->setTableReference($bigqueryTable)
->setRowsLimit(1000)
->setSampleMethod(SampleMethod::RANDOM_START)
->setIdentifyingFields([
(new FieldId())
->setName('name')
]);
$storageConfig = (new StorageConfig())
->setBigQueryOptions($bigQueryOptions);
// Specify the type of info the inspection will look for.
// See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
$personNameInfoType = (new InfoType())
->setName('PERSON_NAME');
$infoTypes = [$personNameInfoType];
// Specify how the content should be inspected.
$inspectConfig = (new InspectConfig())
->setInfoTypes($infoTypes)
->setIncludeQuote(true);
// Specify the action that is triggered when the job completes.
$pubSubAction = (new PublishToPubSub())
->setTopic($topic->name());
$action = (new Action())
->setPubSub($pubSubAction);
// Configure the long running job we want the service to perform.
$inspectJob = (new InspectJobConfig())
->setInspectConfig($inspectConfig)
->setStorageConfig($storageConfig)
->setActions([$action]);
// Listen for job notifications via an existing topic/subscription.
$subscription = $topic->subscription($subscriptionId);
// Submit request
$parent = "projects/$callingProjectId/locations/global";
$job = $dlp->createDlpJob($parent, [
'inspectJob' => $inspectJob
]);
// Poll Pub/Sub using exponential backoff until job finishes
// Consider using an asynchronous execution model such as Cloud Functions
$attempt = 1;
$startTime = time();
do {
foreach ($subscription->pull() as $message) {
if (
isset($message->attributes()['DlpJobName']) &&
$message->attributes()['DlpJobName'] === $job->getName()
) {
$subscription->acknowledge($message);
// Get the updated job. Loop to avoid race condition with DLP API.
do {
$job = $dlp->getDlpJob($job->getName());
} while ($job->getState() == JobState::RUNNING);
break 2; // break from parent do while
}
}
printf('Waiting for job to complete' . PHP_EOL);
// Exponential backoff with max delay of 60 seconds
sleep(min(60, pow(2, ++$attempt)));
} while (time() - $startTime < 600); // 10 minute timeout
// Print finding counts
printf('Job %s status: %s' . PHP_EOL, $job->getName(), JobState::name($job->getState()));
switch ($job->getState()) {
case JobState::DONE:
$infoTypeStats = $job->getInspectDetails()->getResult()->getInfoTypeStats();
if (count($infoTypeStats) === 0) {
printf('No findings.' . PHP_EOL);
} else {
foreach ($infoTypeStats as $infoTypeStat) {
printf(
' Found %s instance(s) of infoType %s' . PHP_EOL,
$infoTypeStat->getCount(),
$infoTypeStat->getInfoType()->getName()
);
}
}
break;
case JobState::FAILED:
printf('Job %s had errors:' . PHP_EOL, $job->getName());
$errors = $job->getErrors();
foreach ($errors as $error) {
var_dump($error->getDetails());
}
break;
case JobState::PENDING:
printf('Job has not completed. Consider a longer timeout or an asynchronous execution model' . PHP_EOL);
break;
default:
printf('Unexpected job state. Most likely, the job is either running or has not yet started.');
}
}
import threading
import google.cloud.dlp
import google.cloud.pubsub
def inspect_bigquery_table_with_sampling(
project: str,
topic_id: str,
subscription_id: str,
min_likelihood: str = None,
max_findings: str = None,
timeout: int = 300,
) -> None:
"""Uses the Data Loss Prevention API to analyze BigQuery data by limiting
the amount of data to be scanned.
Args:
project: The Google Cloud project id to use as a parent resource.
topic_id: The id of the Cloud Pub/Sub topic to which the API will
broadcast job completion. The topic must already exist.
subscription_id: The id of the Cloud Pub/Sub subscription to listen on
while waiting for job completion. The subscription must already
exist and be subscribed to the topic.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
timeout: The number of seconds to wait for a response from the API.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Specify how the content should be inspected. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": [{"name": "PERSON_NAME"}],
"min_likelihood": min_likelihood,
"limits": {"max_findings_per_request": max_findings},
"include_quote": True,
}
# Specify the BigQuery table to be inspected.
# Here we are using public bigquery table.
table_reference = {
"project_id": "bigquery-public-data",
"dataset_id": "usa_names",
"table_id": "usa_1910_current",
}
# Construct a storage_config containing the target BigQuery info.
storage_config = {
"big_query_options": {
"table_reference": table_reference,
"rows_limit": 1000,
"sample_method": "RANDOM_START",
"identifying_fields": [{"name": "name"}],
}
}
# Tell the API where to send a notification when the job is complete.
topic = google.cloud.pubsub.PublisherClient.topic_path(project, topic_id)
actions = [{"pub_sub": {"topic": topic}}]
# Construct the inspect_job, which defines the entire inspect content task.
inspect_job = {
"inspect_config": inspect_config,
"storage_config": storage_config,
"actions": actions,
}
# Convert the project id into full resource ids.
parent = f"projects/{project}/locations/global"
# Call the API
operation = dlp.create_dlp_job(
request={"parent": parent, "inspect_job": inspect_job}
)
print(f"Inspection operation started: {operation.name}")
# Create a Pub/Sub client and find the subscription. The subscription is
# expected to already be listening to the topic.
subscriber = google.cloud.pubsub.SubscriberClient()
subscription_path = subscriber.subscription_path(project, subscription_id)
# Set up a callback to acknowledge a message. This closes around an event
# so that it can signal that it is done and the main thread can continue.
job_done = threading.Event()
def callback(message: google.cloud.pubsub_v1.subscriber.message.Message) -> None:
try:
if message.attributes["DlpJobName"] == operation.name:
# This is the message we're looking for, so acknowledge it.
message.ack()
# Now that the job is done, fetch the results and print them.
job = dlp.get_dlp_job(request={"name": operation.name})
print(f"Job name: {job.name}")
if job.inspect_details.result.info_type_stats:
for finding in job.inspect_details.result.info_type_stats:
print(
f"Info type: {finding.info_type.name}; Count: {finding.count}"
)
else:
print("No findings.")
# Signal to the main thread that we can exit.
job_done.set()
else:
# This is not the message we're looking for.
message.drop()
except Exception as e:
# Because this is executing in a thread, an exception won't be
# noted unless we print it manually.
print(e)
raise
# Register the callback and wait on the event.
subscriber.subscribe(subscription_path, callback=callback)
finished = job_done.wait(timeout=timeout)
if not finished:
print(
"No event received before the timeout. Please verify that the "
"subscription provided is subscribed to the topic provided."
)
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using Google.Cloud.PubSub.V1;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;
public class InspectBigQueryWithSampling
{
public static async Task<DlpJob> InspectAsync(
string projectId,
int maxFindings,
bool includeQuote,
string topicId,
string subId,
Likelihood minLikelihood = Likelihood.Possible,
IEnumerable<FieldId> identifyingFields = null,
IEnumerable<InfoType> infoTypes = null)
{
// Instantiate the dlp client.
var dlp = DlpServiceClient.Create();
// Construct Storage config.
var storageConfig = new StorageConfig
{
BigQueryOptions = new BigQueryOptions
{
TableReference = new BigQueryTable
{
ProjectId = "bigquery-public-data",
DatasetId = "usa_names",
TableId = "usa_1910_current",
},
IdentifyingFields =
{
identifyingFields ?? new FieldId[] { new FieldId { Name = "name" } }
},
RowsLimit = 100,
SampleMethod = BigQueryOptions.Types.SampleMethod.RandomStart
}
};
// Construct the inspect config.
var inspectConfig = new InspectConfig
{
InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } } },
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings,
},
IncludeQuote = includeQuote,
MinLikelihood = minLikelihood
};
// Construct the pubsub action.
var actions = new Action[]
{
new Action
{
PubSub = new Action.Types.PublishToPubSub
{
Topic = $"projects/{projectId}/topics/{topicId}"
}
}
};
// Construct the inspect job config using the actions.
var inspectJob = new InspectJobConfig
{
StorageConfig = storageConfig,
InspectConfig = inspectConfig,
Actions = { actions }
};
// Issue Create Dlp Job Request.
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
ParentAsLocationName = new LocationName(projectId, "global"),
};
// We keep the name of the job that we just created.
var dlpJob = dlp.CreateDlpJob(request);
var jobName = dlpJob.Name;
// Listen to pub/sub for the job.
var subscriptionName = new SubscriptionName(projectId, subId);
var subscriber = await SubscriberClient.CreateAsync(
subscriptionName);
// SimpleSubscriber runs your message handle function on multiple threads to maximize throughput.
await subscriber.StartAsync((PubsubMessage message, CancellationToken cancel) =>
{
if (message.Attributes["DlpJobName"] == jobName)
{
subscriber.StopAsync(cancel);
return Task.FromResult(SubscriberClient.Reply.Ack);
}
else
{
return Task.FromResult(SubscriberClient.Reply.Nack);
}
});
// Get the latest state of the job from the service.
var resultJob = dlp.GetDlpJob(new GetDlpJobRequest
{
DlpJobName = DlpJobName.Parse(jobName)
});
// Parse the response and process results.
System.Console.WriteLine($"Job status: {resultJob.State}");
System.Console.WriteLine($"Job Name: {resultJob.Name}");
var result = resultJob.InspectDetails.Result;
foreach (var infoType in result.InfoTypeStats)
{
System.Console.WriteLine($"Info Type: {infoType.InfoType.Name}");
System.Console.WriteLine($"Count: {infoType.Count}");
}
return resultJob;
}
}
민감한 정보 보호로 생성된 방대한 양의 데이터를 살펴보기 위해 내장된 BigQuery 도구를 사용하여 풍부한 정보를 제공하는 SQL 분석을 실행하거나 Looker Studio와 같은 도구를 사용하여 보고서를 생성할 수 있습니다. 자세한 내용은 민감한 정보 보호 발견 항목 분석 및 보고를 참조하세요. 샘플 쿼리는 BigQuery에서 결과 쿼리를 참조하세요.
민감한 정보 보호에 스토리지 저장소 검사 요청을 보내면 그에 대한 응답으로 DlpJob 객체 인스턴스가 만들어지고 실행됩니다. 데이터의 크기와 지정된 구성에 따라 이러한 작업을 실행하는 데 몇 초, 몇 분, 몇 시간이 소요될 수 있습니다. Pub/Sub 주제에 게시하도록 선택하면(Action에 PublishToPubSub 지정) 작업의 상태가 변경될 때 지정된 이름의 주제로 자동으로 알림이 전송됩니다. Pub/Sub 주제의 이름은 projects/[PROJECT-ID]/topics/[PUBSUB-TOPIC-NAME] 형식으로 지정됩니다.
사용자는 자신이 생성하는 작업에 대해 다음 관리 메서드를 포함하여 완전한 제어 권한을 가집니다.
projects.dlpJobs.cancel 메서드: 현재 진행 중인 작업을 중지합니다. 서버는 작업을 취소하기 위해 최선을 다하지만 성공이 보장되지는 않습니다.작업 및 해당 구성은 삭제할 때까지 유지됩니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2024-02-15(UTC)"],[],[]]
