Mengirimkan hasil tugas pemeriksaan Perlindungan Data Sensitif ke Security Command Center

Panduan ini memandu Anda memeriksa data di Cloud Storage, Firestore dalam mode Datastore (Datastore), atau BigQuery dan mengirim hasil pemeriksaan ke Security Command Center.

Untuk data BigQuery, Anda juga dapat melakukan pembuatan profil, yang berbeda dengan operasi pemeriksaan. Anda juga dapat mengirim profil data ke Security Command Center. Untuk informasi selengkapnya, lihat Memublikasikan profil data ke Security Command Center.

Ringkasan

Security Command Center memungkinkan Anda mengumpulkan data tentang, mengidentifikasi, dan menindaklanjuti ancaman keamanan sebelum dapat menyebabkan kerusakan atau kerugian bisnis. Dengan Security Command Center, Anda dapat melakukan beberapa tindakan terkait keamanan dari satu dasbor terpusat.

Sensitive Data Protection memiliki integrasi bawaan dengan Security Command Center. Saat Anda menggunakan tindakan Sensitive Data Protection untuk memeriksa repositori penyimpanan Google Cloud Anda guna menemukan data sensitif, tindakan ini dapat mengirim hasilnya langsung ke dasbor Security Command Center. Metrik ini ditampilkan di samping metrik keamanan lainnya.

Dengan menyelesaikan langkah-langkah dalam panduan ini, Anda akan melakukan hal berikut:

  • Aktifkan Security Command Center dan Perlindungan Data Sensitif.
  • Siapkan Perlindungan Data Sensitif untuk memeriksa repositori penyimpanan Google Cloud, baik bucket Cloud Storage, tabel BigQuery, maupun jenis Datastore.
  • Konfigurasikan pemindaian Perlindungan Data Sensitif untuk mengirim hasil tugas pemeriksaan ke Security Command Center.

Untuk informasi selengkapnya tentang Security Command Center, lihat dokumentasi Security Command Center.

Jika Anda ingin mengirim hasil pemindaian penemuan—bukan tugas pemeriksaan—ke Security Command Center, lihat dokumentasi untuk membuat profil organisasi, folder, atau project.

Biaya

Dalam dokumen ini, Anda akan menggunakan komponen Google Cloud yang dapat ditagih berikut:

  • Sensitive Data Protection
  • Cloud Storage
  • BigQuery
  • Datastore

Untuk membuat perkiraan biaya berdasarkan proyeksi penggunaan Anda, gunakan kalkulator harga. Pengguna baru Google Cloud mungkin memenuhi syarat untuk mendapatkan uji coba gratis.

Sebelum memulai

Sebelum dapat mengirim hasil pemindaian Sensitive Data Protection ke Security Command Center, Anda harus melakukan setiap hal berikut:

  • Langkah 1: Tetapkan repositori penyimpanan Google Cloud.
  • Langkah 2: Tetapkan peran Identity and Access Management (IAM).
  • Langkah 3: Aktifkan Security Command Center.
  • Langkah 4: Aktifkan Perlindungan Data Sensitif.
  • Langkah 5: Aktifkan Perlindungan Data Sensitif sebagai sumber keamanan untuk Security Command Center.

Langkah-langkah untuk menyiapkan komponen ini dijelaskan di bagian berikut.

Langkah 1: Tetapkan repositori penyimpanan Google Cloud

Pilih apakah Anda ingin memindai repositori penyimpanan Google Cloud Anda sendiri atau contoh. Topik ini memberikan petunjuk untuk kedua skenario tersebut.

Memindai data Anda sendiri

Jika Anda ingin memindai bucket Cloud Storage, tabel BigQuery, atau jenis Datastore yang sudah ada, buka terlebih dahulu project tempat repositori berada. Pada langkah berikutnya, Anda akan mengaktifkan Security Command Center dan Perlindungan Data Sensitif untuk project ini dan organisasinya.

Setelah membuka project yang ingin digunakan, lanjutkan ke Langkah 2 untuk menyiapkan beberapa peran IAM.

Memindai data sampel

Jika Anda ingin memindai set data pengujian, pastikan terlebih dahulu bahwa Anda telah menyiapkan akun penagihan, lalu buat project baru. Untuk menyelesaikan langkah ini, Anda harus memiliki peran Pembuat Project IAM. Pelajari lebih lanjut peran IAM.

  1. Jika Anda belum mengonfigurasi penagihan, siapkan akun penagihan.

    Pelajari cara mengaktifkan penagihan

  2. Buka halaman New Project di konsol Google Cloud.

    Buka Project Baru

  3. Pada menu drop-down Billing account, pilih akun penagihan yang akan ditagih untuk project tersebut.
  4. Pada menu drop-down Organization, pilih organisasi tempat Anda ingin membuat project.
  5. Pada menu drop-down Lokasi, pilih organisasi atau folder tempat Anda ingin membuat project.

Selanjutnya, download dan simpan data sampel:

  1. Buka repositori tutorial fungsi Cloud Run di GitHub.
  2. Klik Clone or download, lalu klik Download ZIP.
  3. Ekstrak file zip yang Anda download.
  4. Buka halaman Storage Browser di konsol Google Cloud.

    Buka Cloud Storage

  5. Klik Create bucket.
  6. Di halaman Create a bucket, beri bucket nama unik, lalu klik Create.
  7. Di halaman Detail bucket, klik Upload folder.
  8. Buka folder dlp-cloud-functions-tutorials-master yang telah Anda ekstrak, buka, lalu pilih folder sample_data. Klik Upload untuk mengupload konten folder ke Cloud Storage.

Catat nama yang Anda berikan ke bucket Cloud Storage untuk nanti. Setelah upload file selesai, Anda siap untuk melanjutkan.

Langkah 2: Tetapkan peran IAM

Untuk menggunakan Perlindungan Data Sensitif guna mengirim hasil pemindaian ke Security Command Center, Anda memerlukan peran IAM Security Center Admin dan Sensitive Data Protection Jobs Editor. Bagian ini menjelaskan cara menambahkan peran. Untuk menyelesaikan bagian ini, Anda harus memiliki peran IAM Organization Administrator.

  1. Buka halaman IAM.

    Buka IAM

  2. Di tab Lihat menurut akun utama, temukan Akun Google Anda, lalu klik Edit akun utama.

  3. Tambahkan peran Security Center Admin dan Sensitive Data Protection Jobs Editor:

    1. Di panel Edit akses, klik Tambahkan peran lain.
    2. Di daftar Select a role, telusuri Security Center Admin, lalu pilih peran tersebut.
    3. Klik Add another role.
    4. Di daftar Select a role, telusuri DLP Jobs Editor, lalu pilih peran tersebut.
    5. Klik Simpan.

Sekarang Anda memiliki peran Editor Tugas Sensitive Data Protection dan Security Center Admin untuk organisasi Anda. Peran ini memungkinkan Anda menyelesaikan tugas di bagian lain topik ini.

Langkah 3: Aktifkan Security Command Center

  1. Buka halaman Security Command Center di konsol Google Cloud.

    Buka Security Command Center

  2. Pada menu drop-down Organization, pilih organisasi yang ingin Anda aktifkan Perlindungan Data Sensitif, lalu klik Select.

  3. Di halaman Enable asset discovery yang muncul, pilih All current and future projects, lalu klik Enable. Pesan akan ditampilkan bahwa Perlindungan Data Sensitif sedang memulai penemuan aset.

Setelah penemuan aset selesai, Sensitive Data Protection akan menampilkan aset Google Cloud yang didukung. Penemuan aset mungkin memerlukan waktu beberapa menit, dan Anda mungkin perlu memuat ulang halaman untuk menampilkan aset.

Untuk informasi selengkapnya tentang cara mengaktifkan Security Command Center, lihat dokumentasi Security Command Center.

Langkah 4: Aktifkan Perlindungan Data Sensitif

Aktifkan Perlindungan Data Sensitif untuk project yang ingin Anda pindai. Project harus berada dalam organisasi yang sama dengan yang telah Anda aktifkan Security Command Center-nya. Untuk mengaktifkan Sensitive Data Protection menggunakan konsol Google Cloud:

  1. Di konsol Google Cloud, buka halaman Aktifkan akses ke API.

    Mengaktifkan API

  2. Di toolbar, pilih project dari Langkah 1 panduan ini. Project harus berisi bucket Cloud Storage, tabel BigQuery, atau jenis Datastore yang ingin Anda pindai.
  3. Klik Berikutnya.
  4. Klik Aktifkan.

Sensitive Data Protection kini diaktifkan untuk project Anda.

Langkah 5: Aktifkan Perlindungan Data Sensitif sebagai layanan terintegrasi untuk Security Command Center

Untuk melihat temuan pemindaian Sensitive Data Protection di Security Command Center, aktifkan Sensitive Data Protection sebagai layanan terintegrasi. Untuk mengetahui informasi selengkapnya, lihat Menambahkan layanan terintegrasi Google Cloud dalam dokumentasi Security Command Center.

Temuan untuk Sensitive Data Protection ditampilkan di halaman Temuan di Security Command Center.

Mengonfigurasi dan menjalankan pemindaian inspeksi Perlindungan Data Sensitif

Di bagian ini, Anda akan mengonfigurasi dan menjalankan tugas pemeriksaan Perlindungan Data Sensitif.

Tugas inspeksi yang Anda konfigurasikan di sini akan menginstruksikan Sensitive Data Protection untuk memindai contoh data yang disimpan di Cloud Storage atau data Anda sendiri yang disimpan di Cloud Storage, Datastore, atau BigQuery. Konfigurasi tugas yang Anda tentukan juga merupakan tempat Anda menginstruksikan Sensitive Data Protection untuk menyimpan hasil pemindaian ke Security Command Center.

Langkah 1: Catat ID project Anda

  1. Buka konsol Google Cloud.

    Buka konsol Google Cloud.

  2. Klik Pilih.
  3. Pada menu drop-down Select from, pilih organisasi tempat Anda mengaktifkan Security Command Center.
  4. Di bagian ID, salin project ID untuk project yang berisi data yang ingin Anda pindai.
  5. Di bagian Nama, klik project untuk memilihnya.

Langkah 2: Buka API Explorer dan konfigurasikan tugas

  1. Buka API Explorer di halaman referensi untuk metode dlpJobs.create dengan mengklik tombol berikut:

    Membuka API Explorer

  2. Di kotak parent, masukkan kode berikut, dengan PROJECT_ID adalah project ID yang Anda catat di Langkah 1: 
    projects/PROJECT_ID

Ganti konten kolom Request body dengan JSON berikut untuk jenis data yang ingin Anda gunakan: data sampel di bucket Cloud Storage, atau data Anda sendiri yang disimpan di Cloud Storage, Datastore, atau BigQuery.

Data sampel

Jika Anda membuat bucket Cloud Storage untuk menyimpan data sampel, salin JSON berikut, lalu tempelkan ke kolom Isi permintaan. Ganti BUCKET_NAME dengan nama yang Anda berikan ke bucket Cloud Storage:

{
  "inspectJob":{
    "storageConfig":{
      "cloudStorageOptions":{
        "fileSet":{
          "url":"gs://BUCKET_NAME/**"
        }
      }
    },
    "inspectConfig":{
      "infoTypes":[
        {
          "name":"EMAIL_ADDRESS"
        },
        {
          "name":"PERSON_NAME"
        },
        {
          "name": "LOCATION"
        },
        {
          "name":"PHONE_NUMBER"
        }
      ],
      "includeQuote":true,
      "minLikelihood":"UNLIKELY",
      "limits":{
        "maxFindingsPerRequest":100
      }
    },
    "actions":[
      {
        "publishSummaryToCscc":{

        }
      }
    ]
  }
}

Data Cloud Storage

Untuk memindai bucket Cloud Storage Anda sendiri, salin JSON berikut dan tempelkan ke kolom Isi permintaan.

Ganti PATH_NAME dengan jalur ke lokasi yang ingin Anda pindai. Untuk memindai secara berulang, akhiri jalur dengan dua tanda bintang, misalnya, gs://path_to_files/**. Untuk memindai direktori tertentu dan tidak lebih dalam, akhiri jalur dengan satu tanda bintang, misalnya, gs://path_to_files/*.

{
  "inspectJob":{
    "storageConfig":{
      "cloudStorageOptions":{
        "fileSet":{
          "url":"gs://PATH_NAME"
        }
      }
    },
    "inspectConfig":{
      "infoTypes":[
        {
          "name":"EMAIL_ADDRESS"
        },
        {
          "name":"PERSON_NAME"
        },
        {
          "name": "LOCATION"
        },
        {
          "name":"PHONE_NUMBER"
        }
      ],
      "includeQuote":true,
      "minLikelihood":"UNLIKELY",
      "limits":{
        "maxFindingsPerRequest":100
      }
    },
    "actions":[
      {
        "publishSummaryToCscc":{

        }
      }
    ]
  }
}

Untuk mempelajari opsi pemindaian yang tersedia lebih lanjut, lihat Memeriksa penyimpanan dan database untuk menemukan data sensitif.

Data datastore

Untuk memindai data Anda sendiri yang disimpan di Datastore, salin JSON berikut dan tempelkan ke kolom Isi permintaan.

Ganti DATASTORE_KIND dengan nama jenis Datastore. Anda juga dapat mengganti NAMESPACE_ID dan PROJECT_ID dengan namespace dan ID project, atau Anda dapat menghapus "partitionID" sepenuhnya jika mau.

{
  "inspectJob":{
    "storageConfig":{
      "datastoreOptions":{
        "kind":{
          "name":"DATASTORE_KIND"
        },
        "partitionId":{
          "namespaceId":"NAMESPACE_ID",
          "projectId":"PROJECT_ID"
        }
      }
    },
    "inspectConfig":{
      "infoTypes":[
        {
          "name":"EMAIL_ADDRESS"
        },
        {
          "name":"PERSON_NAME"
        },
        {
          "name": "LOCATION"
        },
        {
          "name":"PHONE_NUMBER"
        }
      ],
      "includeQuote":true,
      "minLikelihood":"UNLIKELY",
      "limits":{
        "maxFindingsPerRequest":100
      }
    },
    "actions":[
      {
        "publishSummaryToCscc":{

        }
      }
    ]
  }
}

Untuk mempelajari opsi pemindaian yang tersedia lebih lanjut, lihat Memeriksa penyimpanan dan database untuk menemukan data sensitif.

Data BigQuery

Untuk memindai tabel BigQuery Anda sendiri, salin JSON berikut dan tempelkan ke kolom Isi permintaan.

Ganti PROJECT_ID, BIGQUERY_DATASET_NAME, dan BIGQUERY_TABLE_NAME dengan ID project serta nama set data dan tabel BigQuery.

{
  "inspectJob":
  {
    "storageConfig":
    {
      "bigQueryOptions":
      {
        "tableReference":
        {
          "projectId": "PROJECT_ID",
          "datasetId": "BIGQUERY_DATASET_NAME",
          "tableId": "BIGQUERY_TABLE_NAME"
        }
      }
    },
    "inspectConfig":
    {
      "infoTypes":
      [
        {
          "name": "EMAIL_ADDRESS"
        },
        {
          "name": "PERSON_NAME"
        },
        {
          "name": "LOCATION"
        },
        {
          "name": "PHONE_NUMBER"
        }
      ],
      "includeQuote": true,
      "minLikelihood": "UNLIKELY",
      "limits":
      {
        "maxFindingsPerRequest": 100
      }
    },
    "actions":
    [
      {
        "publishSummaryToCscc":
        {
        }
      }
    ]
  }
}

Untuk mempelajari opsi pemindaian yang tersedia lebih lanjut, lihat Memeriksa penyimpanan dan database untuk menemukan data sensitif.

Langkah 3: Jalankan permintaan untuk memulai tugas inspeksi

Setelah Anda mengonfigurasi tugas dengan mengikuti langkah-langkah sebelumnya, klik Execute untuk mengirim permintaan. Jika permintaan berhasil, respons akan muncul di bawah permintaan dengan kode sukses dan objek JSON yang menunjukkan status tugas Perlindungan Data Sensitif yang Anda buat.

Memeriksa status pemindaian pemeriksaan Perlindungan Data Sensitif

Respons terhadap permintaan pemindaian Anda menyertakan ID tugas tugas pemindaian pemeriksaan sebagai kunci "name", dan status saat ini dari tugas pemeriksaan sebagai kunci "state". Segera setelah Anda mengirimkan permintaan, status tugas adalah "PENDING".

Setelah Anda mengirimkan permintaan pemindaian, pemindaian konten Anda akan segera dimulai.

Untuk memeriksa status tugas inspeksi:

  1. Buka API Explorer di halaman referensi untuk metode dlpJobs.get dengan mengklik tombol berikut:

    Membuka API Explorer

  2. Di kotak name, ketik nama tugas dari respons JSON ke permintaan pemindaian dalam bentuk berikut: 
    projects/PROJECT_ID/dlpJobs/JOB_ID
     ID tugas dalam bentuk i-1234567890123456789.
  3. Untuk mengirimkan permintaan, klik Execute.

Jika kunci "state" objek JSON respons menunjukkan bahwa tugasnya adalah "DONE", tugas inspeksi telah selesai.

Untuk melihat JSON respons lainnya, scroll halaman ke bawah. Di bagian "result" > "infoTypeStats", setiap jenis informasi yang tercantum harus memiliki "count" yang sesuai. Jika tidak, pastikan Anda memasukkan JSON dengan akurat, dan bahwa jalur atau lokasi ke data Anda sudah benar.

Setelah tugas inspeksi selesai, Anda dapat melanjutkan ke bagian berikutnya dalam panduan ini untuk melihat hasil pemindaian di Security Command Center.

Contoh kode: memeriksa bucket Cloud Storage

Contoh ini menunjukkan cara menggunakan DLP API untuk membuat tugas pemeriksaan yang memeriksa bucket Cloud Storage dan mengirim temuan ke Security Command Center.

C#

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


using System.Collections.Generic;
using System.Linq;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;

public class InspectStorageWithSCCIntegration
{
    public static DlpJob SendGcsData(
        string projectId,
        string gcsPath,
        Likelihood minLikelihood = Likelihood.Unlikely,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Specify the GCS file to be inspected.
        var storageConfig = new StorageConfig
        {
            CloudStorageOptions = new CloudStorageOptions
            {
                FileSet = new CloudStorageOptions.Types.FileSet
                {
                    Url = gcsPath
                }
            }
        };

        // Specify the type of info to be inspected and construct the inspect config.
        var inspectConfig = new InspectConfig
        {
            InfoTypes =
            {
                infoTypes ?? new InfoType[]
                {
                    new InfoType { Name = "EMAIL_ADDRESS" },
                    new InfoType { Name = "PERSON_NAME" },
                    new InfoType { Name = "LOCATION" },
                    new InfoType { Name = "PHONE_NUMBER" }
                }
            },
            IncludeQuote = true,
            MinLikelihood = minLikelihood,
            Limits = new FindingLimits
            {
                MaxFindingsPerRequest = 100
            }
        };

        // Construct the SCC action which will be performed after inspecting the storage.
        var actions = new Action[]
        {
            new Action
            {
                PublishSummaryToCscc = new Action.Types.PublishSummaryToCscc()
            }
        };

        // Construct the inspect job config using storage config, inspect config and action.
        var inspectJob = new InspectJobConfig
        {
            StorageConfig = storageConfig,
            InspectConfig = inspectConfig,
            Actions = { actions }
        };

        // Construct the request.
        var request = new CreateDlpJobRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            InspectJob = inspectJob
        };

        // Call the API.
        DlpJob response = dlp.CreateDlpJob(request);

        return response;
    }
}

Go

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// inspectGCSFileSendToScc inspects sensitive data in a Google Cloud Storage (GCS) file
// and sends the inspection results to Google Cloud Security Command Center (SCC) for further analysis.
func inspectGCSFileSendToScc(w io.Writer, projectID, gcsPath string) error {
	// projectID := "my-project-id"
	// gcsPath := "gs://" + "your-bucket-name" + "path/to/file.txt"

	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.
	cloudStorageOptions := &dlppb.CloudStorageOptions{
		FileSet: &dlppb.CloudStorageOptions_FileSet{
			Url: gcsPath,
		},
	}

	// storageCfg represents the configuration for data inspection in various storage types.
	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
	infoTypes := []*dlppb.InfoType{
		{Name: "EMAIL_ADDRESS"},
		{Name: "PERSON_NAME"},
		{Name: "LOCATION"},
		{Name: "PHONE_NUMBER"},
	}

	// The minimum likelihood required before returning a match.
	minLikelihood := dlppb.Likelihood_UNLIKELY

	// The maximum number of findings to report (0 = server maximum).
	findingLimits := &dlppb.InspectConfig_FindingLimits{
		MaxFindingsPerItem: 100,
	}

	inspectConfig := &dlppb.InspectConfig{
		InfoTypes:     infoTypes,
		MinLikelihood: minLikelihood,
		Limits:        findingLimits,
		IncludeQuote:  true,
	}

	// Specify the action that is triggered when the job completes.
	action := &dlppb.Action{
		Action: &dlppb.Action_PublishSummaryToCscc_{
			PublishSummaryToCscc: &dlppb.Action_PublishSummaryToCscc{},
		},
	}

	// Configure the inspection 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,
		},
	}

	// Send the request.
	resp, err := client.CreateDlpJob(ctx, req)
	if err != nil {
		return err
	}

	// Print the result.
	fmt.Fprintf(w, "Job created successfully: %v", resp.Name)
	return nil
}

Java

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.Action;
import com.google.privacy.dlp.v2.CloudStorageOptions;
import com.google.privacy.dlp.v2.CreateDlpJobRequest;
import com.google.privacy.dlp.v2.DlpJob;
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 java.io.IOException;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class InspectGcsFileSendToScc {

  private static final int TIMEOUT_MINUTES = 15;

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    // The Google Cloud project id to use as a parent resource.
    String projectId = "your-project-id";
    // The name of the file in the Google Cloud Storage bucket.
    String gcsPath = "gs://" + "your-bucket-name" + "path/to/file.txt";
    createJobSendToScc(projectId, gcsPath);
  }

  // Creates a DLP Job to scan the sample data stored in a Cloud Storage and save its scan results
  // to Security Command Center.
  public static void createJobSendToScc(String projectId, String gcsPath)
      throws IOException, InterruptedException {
    // 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 dlpServiceClient = DlpServiceClient.create()) {

      // Specify the GCS file to be inspected.
      CloudStorageOptions cloudStorageOptions =
          CloudStorageOptions.newBuilder()
              .setFileSet(CloudStorageOptions.FileSet.newBuilder().setUrl(gcsPath))
              .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("EMAIL_ADDRESS", "PERSON_NAME", "LOCATION", "PHONE_NUMBER")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      // The minimum likelihood required before returning a match.
      // See: https://cloud.google.com/dlp/docs/likelihood
      Likelihood minLikelihood = Likelihood.UNLIKELY;

      // The maximum number of findings to report (0 = server maximum)
      InspectConfig.FindingLimits findingLimits =
          InspectConfig.FindingLimits.newBuilder().setMaxFindingsPerItem(100).build();

      InspectConfig inspectConfig =
          InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .setIncludeQuote(true)
              .setMinLikelihood(minLikelihood)
              .setLimits(findingLimits)
              .build();

      // Specify the action that is triggered when the job completes.
      Action.PublishSummaryToCscc publishSummaryToCscc =
          Action.PublishSummaryToCscc.getDefaultInstance();
      Action action = Action.newBuilder().setPublishSummaryToCscc(publishSummaryToCscc).build();

      // Configure the inspection job we want the service to perform.
      InspectJobConfig inspectJobConfig =
          InspectJobConfig.newBuilder()
              .setInspectConfig(inspectConfig)
              .setStorageConfig(storageConfig)
              .addActions(action)
              .build();

      // Construct the job creation request to be sent by the client.
      CreateDlpJobRequest createDlpJobRequest =
          CreateDlpJobRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setInspectJob(inspectJobConfig)
              .build();

      // Send the job creation request and process the response.
      DlpJob response = dlpServiceClient.createDlpJob(createDlpJobRequest);
      // Get the current time.
      long startTime = System.currentTimeMillis();

      // Check if the job state is DONE.
      while (response.getState() != DlpJob.JobState.DONE) {
        // Sleep for 30 second.
        Thread.sleep(30000);

        // Get the updated job status.
        response = dlpServiceClient.getDlpJob(response.getName());

        // Check if the timeout duration has exceeded.
        long elapsedTime = System.currentTimeMillis() - startTime;
        if (TimeUnit.MILLISECONDS.toMinutes(elapsedTime) >= TIMEOUT_MINUTES) {
          System.out.printf("Job did not complete within %d minutes.%n", TIMEOUT_MINUTES);
          break;
        }
      }
      // Print the results.
      System.out.println("Job status: " + response.getState());
      System.out.println("Job name: " + response.getName());
      InspectDataSourceDetails.Result result = response.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());
      }
    }
  }
}

Node.js

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlpClient = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'your-project-id';

// The name of the file in the bucket
// const gcsPath = 'gcs-file-path';

async function inspectGCSSendToScc() {
  // Specify the storage configuration object with GCS URL.
  const storageConfig = {
    cloudStorageOptions: {
      fileSet: {
        url: gcsPath,
      },
    },
  };

  // Construct the info types to look for in the GCS file.
  const infoTypes = [
    {name: 'EMAIL_ADDRESS'},
    {name: 'PERSON_NAME'},
    {name: 'LOCATION'},
    {name: 'PHONE_NUMBER'},
  ];

  // Construct the inspection configuration.
  const inspectConfig = {
    infoTypes,
    minLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.UNLIKELY,
    limits: {
      maxFindingsPerItem: 100,
    },
  };

  // Specify the action that is triggered when the job completes.
  const action = {
    publishSummaryToCscc: {},
  };

  // Configure the inspection job we want the service to perform.
  const jobConfig = {
    inspectConfig,
    storageConfig,
    actions: [action],
  };

  // Construct the job creation request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectJob: jobConfig,
  };

  // Send the job creation request and process the response.
  const [jobsResponse] = await dlpClient.createDlpJob(request);
  const jobName = jobsResponse.name;

  // Waiting for a maximum of 15 minutes for the job to get complete.
  let job;
  let numOfAttempts = 30;
  while (numOfAttempts > 0) {
    // Fetch DLP Job status
    [job] = await dlpClient.getDlpJob({name: jobName});

    // Check if the job has completed.
    if (job.state === 'DONE') {
      break;
    }
    if (job.state === 'FAILED') {
      console.log('Job Failed, Please check the configuration.');
      return;
    }
    // Sleep for a short duration before checking the job status again.
    await new Promise(resolve => {
      setTimeout(() => resolve(), 30000);
    });
    numOfAttempts -= 1;
  }

  // Print out the results.
  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 inspectGCSSendToScc();

PHP

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

use Google\Cloud\Dlp\V2\CloudStorageOptions;
use Google\Cloud\Dlp\V2\CloudStorageOptions\FileSet;
use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishSummaryToCscc;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\DlpJob\JobState;

/**
 * (GCS) Send Cloud DLP scan results to Security Command Center.
 * Using Cloud Data Loss Prevention to scan specific Google Cloud resources and send data to Security Command Center.
 *
 * @param string $callingProjectId  The project ID to run the API call under.
 * @param string $gcsUri            GCS file to be inspected.
 */
function inspect_gcs_send_to_scc(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $gcsUri = 'gs://GOOGLE_STORAGE_BUCKET_NAME/dlp_sample.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Construct the items to be inspected.
    $cloudStorageOptions = (new CloudStorageOptions())
        ->setFileSet((new FileSet())
            ->setUrl($gcsUri));

    $storageConfig = (new StorageConfig())
        ->setCloudStorageOptions(($cloudStorageOptions));

    // Specify the type of info the inspection will look for.
    $infoTypes = [
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('PERSON_NAME'),
        (new InfoType())->setName('LOCATION'),
        (new InfoType())->setName('PHONE_NUMBER')
    ];

    // Specify how the content should be inspected.
    $inspectConfig = (new InspectConfig())
        ->setMinLikelihood(likelihood::UNLIKELY)
        ->setLimits((new FindingLimits())
            ->setMaxFindingsPerRequest(100))
        ->setInfoTypes($infoTypes)
        ->setIncludeQuote(true);

    // Specify the action that is triggered when the job completes.
    $action = (new Action())
        ->setPublishSummaryToCscc(new PublishSummaryToCscc());

    // Construct inspect job config to run.
    $inspectJobConfig = (new InspectJobConfig())
        ->setInspectConfig($inspectConfig)
        ->setStorageConfig($storageConfig)
        ->setActions([$action]);

    // Send the job creation request and process the response.
    $parent = "projects/$callingProjectId/locations/global";
    $job = $dlp->createDlpJob($parent, [
        'inspectJob' => $inspectJobConfig
    ]);

    $numOfAttempts = 10;
    do {
        printf('Waiting for job to complete' . PHP_EOL);
        sleep(10);
        $job = $dlp->getDlpJob($job->getName());
        if ($job->getState() == JobState::DONE) {
            break;
        }
        $numOfAttempts--;
    } while ($numOfAttempts > 0);

    // 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.');
    }
}

Python

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import time
from typing import List

import google.cloud.dlp


def inspect_gcs_send_to_scc(
    project: str,
    bucket: str,
    info_types: List[str],
    max_findings: int = 100,
) -> None:
    """
    Uses the Data Loss Prevention API to inspect Google Cloud Storage
    data and send the results to Google Security Command Center.
    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.
        info_types: A list of strings representing infoTypes to inspect for.
            A full list of infoType categories can be fetched from the API.
        max_findings: The maximum number of findings to report; 0 = no maximum.
    """
    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries.
    info_types = [{"name": info_type} for info_type in info_types]

    # Construct the configuration dictionary.
    inspect_config = {
        "info_types": info_types,
        "min_likelihood": google.cloud.dlp_v2.Likelihood.UNLIKELY,
        "limits": {"max_findings_per_request": max_findings},
        "include_quote": True,
    }

    # Construct a cloud_storage_options dictionary with the bucket's URL.
    url = f"gs://{bucket}"
    storage_config = {"cloud_storage_options": {"file_set": {"url": url}}}

    # Tell the API where to send a notification when the job is complete.
    actions = [{"publish_summary_to_cscc": {}}]

    # Construct the job definition.
    job = {
        "inspect_config": inspect_config,
        "storage_config": storage_config,
        "actions": actions,
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.create_dlp_job(
        request={
            "parent": parent,
            "inspect_job": job,
        }
    )
    print(f"Inspection Job started : {response.name}")

    job_name = response.name

    # Waiting for maximum 15 minutes for the job to get complete.
    no_of_attempts = 30
    while no_of_attempts > 0:
        # Get the DLP job status.
        job = dlp.get_dlp_job(request={"name": job_name})
        # Check if the job has completed.
        if job.state == google.cloud.dlp_v2.DlpJob.JobState.DONE:
            break
        elif job.state == google.cloud.dlp_v2.DlpJob.JobState.FAILED:
            print("Job Failed, Please check the configuration.")
            return

        # Sleep for a short duration before checking the job status again.
        time.sleep(30)
        no_of_attempts -= 1

    # Print out the results.
    print(f"Job name: {job.name}")
    result = job.inspect_details.result
    print("Processed Bytes: ", result.processed_bytes)
    if result.info_type_stats:
        for stats in result.info_type_stats:
            print(f"Info type: {stats.info_type.name}")
            print(f"Count: {stats.count}")
    else:
        print("No findings.")

Contoh kode: memeriksa tabel BigQuery

Contoh ini menunjukkan cara menggunakan DLP API untuk membuat tugas inspeksi yang memeriksa tabel BigQuery dan mengirim temuan ke Security Command Center.

C#

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;

public class InspectBigQueryWithSCCIntegration
{
    public static DlpJob SendBigQueryData(
        string projectId,
        Likelihood minLikelihood = Likelihood.Unlikely,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the storage config by providing the table to be inspected.
        var storageConfig = new StorageConfig
        {
            BigQueryOptions = new BigQueryOptions
            {
                TableReference = new BigQueryTable
                {
                    ProjectId = "bigquery-public-data",
                    DatasetId = "usa_names",
                    TableId = "usa_1910_current",
                }
            }
        };

        // Construct the inspect config by specifying the type of info to be inspected.
        var inspectConfig = new InspectConfig
        {
            InfoTypes =
            {
                infoTypes ?? new InfoType[]
                {
                    new InfoType { Name = "EMAIL_ADDRESS" },
                    new InfoType { Name = "PERSON_NAME" }
                }
            },
            IncludeQuote = true,
            MinLikelihood = minLikelihood,
            Limits = new FindingLimits
            {
                MaxFindingsPerRequest = 100
            }
        };

        // Construct the SCC action which will be performed after inspecting the source.
        var actions = new Action[]
        {
            new Action
            {
                PublishSummaryToCscc = new Action.Types.PublishSummaryToCscc()
            }
        };

        // Construct the inspect job config using storage config, inspect config and action.
        var inspectJob = new InspectJobConfig
        {
            StorageConfig = storageConfig,
            InspectConfig = inspectConfig,
            Actions = { actions }
        };

        // Construct the request.
        var request = new CreateDlpJobRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            InspectJob = inspectJob
        };

        // Call the API.
        DlpJob response = dlp.CreateDlpJob(request);

        System.Console.WriteLine($"Job created successfully. Job name: {response.Name}");

        return response;
    }
}

Go

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// inspectBigQuerySendToScc configures the inspection job that instructs Cloud DLP to scan data stored in BigQuery,
// and also instructs Cloud DLP to save its scan results to Security Command Center.
func inspectBigQuerySendToScc(w io.Writer, projectID, bigQueryDatasetId, bigQueryTableId string) error {
	// projectID := "my-project-id"
	// bigQueryDatasetId := "your-project-bigquery-dataset"
	// bigQueryTableId := "your-project-bigquery_table"

	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: projectID,
		DatasetId: bigQueryDatasetId,
		TableId:   bigQueryTableId,
	}

	bigQueryOptions := &dlppb.BigQueryOptions{
		TableReference: tableReference,
	}

	// Specify the type of storage that you have configured.
	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: "EMAIL_ADDRESS"},
		{Name: "PERSON_NAME"},
		{Name: "LOCATION"},
		{Name: "PHONE_NUMBER"},
	}

	// The minimum likelihood required before returning a match.
	minLikelihood := dlppb.Likelihood_UNLIKELY

	// The maximum number of findings to report (0 = server maximum).
	findingLimits := &dlppb.InspectConfig_FindingLimits{
		MaxFindingsPerItem: 100,
	}

	// Specify how the content should be inspected.
	inspectConfig := &dlppb.InspectConfig{
		InfoTypes:     infoTypes,
		MinLikelihood: minLikelihood,
		Limits:        findingLimits,
		IncludeQuote:  true,
	}

	// Specify the action that is triggered when the job completes.
	action := &dlppb.Action{
		Action: &dlppb.Action_PublishSummaryToCscc_{
			PublishSummaryToCscc: &dlppb.Action_PublishSummaryToCscc{},
		},
	}

	// Configure the inspection 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,
		},
	}

	// Send the request.
	resp, err := client.CreateDlpJob(ctx, req)
	if err != nil {
		return err
	}

	// Print the result
	fmt.Fprintf(w, "Job created successfully: %v", resp.Name)
	return nil
}

Java

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


import com.google.cloud.dlp.v2.DlpServiceClient;
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.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 java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class InspectBigQuerySendToScc {

  private static final int TIMEOUT_MINUTES = 15;

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    // The Google Cloud project id to use as a parent resource.
    String projectId = "your-project-id";
    // The BigQuery dataset id to be used and the reference table name to be inspected.
    String bigQueryDatasetId = "your-project-bigquery-dataset";
    String bigQueryTableId = "your-project-bigquery_table";
    inspectBigQuerySendToScc(projectId, bigQueryDatasetId, bigQueryTableId);
  }

  // Inspects a BigQuery Table to send data to Security Command Center.
  public static void inspectBigQuerySendToScc(
      String projectId, String bigQueryDatasetId, String bigQueryTableId) throws Exception {
    // 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 dlpServiceClient = 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.
      List<InfoType> infoTypes =
          Stream.of("EMAIL_ADDRESS", "PERSON_NAME", "LOCATION", "PHONE_NUMBER")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      // The minimum likelihood required before returning a match.
      Likelihood minLikelihood = Likelihood.UNLIKELY;

      // The maximum number of findings to report (0 = server maximum)
      InspectConfig.FindingLimits findingLimits =
          InspectConfig.FindingLimits.newBuilder().setMaxFindingsPerItem(100).build();

      // Specify how the content should be inspected.
      InspectConfig inspectConfig =
          InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .setIncludeQuote(true)
              .setMinLikelihood(minLikelihood)
              .setLimits(findingLimits)
              .build();

      // Specify the action that is triggered when the job completes.
      Action.PublishSummaryToCscc publishSummaryToCscc =
          Action.PublishSummaryToCscc.getDefaultInstance();
      Action action = Action.newBuilder().setPublishSummaryToCscc(publishSummaryToCscc).build();

      // Configure the inspection job we want the service to perform.
      InspectJobConfig inspectJobConfig =
          InspectJobConfig.newBuilder()
              .setInspectConfig(inspectConfig)
              .setStorageConfig(storageConfig)
              .addActions(action)
              .build();

      // Construct the job creation request to be sent by the client.
      CreateDlpJobRequest createDlpJobRequest =
          CreateDlpJobRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setInspectJob(inspectJobConfig)
              .build();

      // Send the job creation request and process the response.
      DlpJob response = dlpServiceClient.createDlpJob(createDlpJobRequest);

      // Get the current time.
      long startTime = System.currentTimeMillis();

      // Check if the job state is DONE.
      while (response.getState() != DlpJob.JobState.DONE) {
        // Sleep for 30 second.
        Thread.sleep(30000);

        // Get the updated job status.
        response = dlpServiceClient.getDlpJob(response.getName());

        // Check if the timeout duration has exceeded.
        long elapsedTime = System.currentTimeMillis() - startTime;
        if (TimeUnit.MILLISECONDS.toMinutes(elapsedTime) >= TIMEOUT_MINUTES) {
          System.out.printf("Job did not complete within %d minutes.%n", TIMEOUT_MINUTES);
          break;
        }
      }
      // Print the results.
      System.out.println("Job status: " + response.getState());
      System.out.println("Job name: " + response.getName());
      InspectDataSourceDetails.Result result = response.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());
      }
    }
  }
}

Node.js

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under.
// const projectId = "your-project-id";

// 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';

async function inspectBigQuerySendToScc() {
  // Specify the storage configuration object with big query table.
  const storageItem = {
    bigQueryOptions: {
      tableReference: {
        projectId: dataProjectId,
        datasetId: datasetId,
        tableId: tableId,
      },
    },
  };

  // Specify the type of info the inspection will look for.
  const infoTypes = [
    {name: 'EMAIL_ADDRESS'},
    {name: 'PERSON_NAME'},
    {name: 'LOCATION'},
    {name: 'PHONE_NUMBER'},
  ];

  // Construct inspect configuration.
  const inspectConfig = {
    infoTypes: infoTypes,
    includeQuote: true,
    minLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.UNLIKELY,
    limits: {
      maxFindingsPerItem: 100,
    },
  };

  // Specify the action that is triggered when the job completes.
  const action = {
    publishSummaryToCscc: {
      enable: true,
    },
  };

  // Configure the inspection job we want the service to perform.
  const inspectJobConfig = {
    inspectConfig: inspectConfig,
    storageConfig: storageItem,
    actions: [action],
  };

  // Construct the job creation request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectJob: inspectJobConfig,
  };

  // Send the job creation request and process the response.
  const [jobsResponse] = await dlp.createDlpJob(request);
  const jobName = jobsResponse.name;

  // Waiting for a maximum of 15 minutes for the job to get complete.
  let job;
  let numOfAttempts = 30;
  while (numOfAttempts > 0) {
    // Fetch DLP Job status
    [job] = await dlp.getDlpJob({name: jobName});

    // Check if the job has completed.
    if (job.state === 'DONE') {
      break;
    }
    if (job.state === 'FAILED') {
      console.log('Job Failed, Please check the configuration.');
      return;
    }
    // Sleep for a short duration before checking the job status again.
    await new Promise(resolve => {
      setTimeout(() => resolve(), 30000);
    });
    numOfAttempts -= 1;
  }

  // Print out the results.
  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 inspectBigQuerySendToScc();

PHP

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishSummaryToCscc;
use Google\Cloud\Dlp\V2\BigQueryOptions;
use Google\Cloud\Dlp\V2\BigQueryTable;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\DlpJob\JobState;

/**
 * (BIGQUERY) Send Cloud DLP scan results to Security Command Center.
 * Using Cloud Data Loss Prevention to scan specific Google Cloud resources and send data to Security Command Center.
 *
 * @param string $callingProjectId  The project ID to run the API call under.
 * @param string $projectId         The ID of the Project.
 * @param string $datasetId         The ID of the BigQuery Dataset.
 * @param string $tableId           The ID of the BigQuery Table to be inspected.
 */
function inspect_bigquery_send_to_scc(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $projectId,
    string $datasetId,
    string $tableId
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Construct the items to be inspected.
    $bigqueryTable = (new BigQueryTable())
        ->setProjectId($projectId)
        ->setDatasetId($datasetId)
        ->setTableId($tableId);
    $bigQueryOptions = (new BigQueryOptions())
        ->setTableReference($bigqueryTable);

    $storageConfig = (new StorageConfig())
        ->setBigQueryOptions(($bigQueryOptions));

    // Specify the type of info the inspection will look for.
    $infoTypes = [
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('PERSON_NAME'),
        (new InfoType())->setName('LOCATION'),
        (new InfoType())->setName('PHONE_NUMBER')
    ];

    // Specify how the content should be inspected.
    $inspectConfig = (new InspectConfig())
        ->setMinLikelihood(likelihood::UNLIKELY)
        ->setLimits((new FindingLimits())
            ->setMaxFindingsPerRequest(100))
        ->setInfoTypes($infoTypes)
        ->setIncludeQuote(true);

    // Specify the action that is triggered when the job completes.
    $action = (new Action())
        ->setPublishSummaryToCscc(new PublishSummaryToCscc());

    // Configure the inspection job we want the service to perform.
    $inspectJobConfig = (new InspectJobConfig())
        ->setInspectConfig($inspectConfig)
        ->setStorageConfig($storageConfig)
        ->setActions([$action]);

    // Send the job creation request and process the response.
    $parent = "projects/$callingProjectId/locations/global";
    $job = $dlp->createDlpJob($parent, [
        'inspectJob' => $inspectJobConfig
    ]);

    $numOfAttempts = 10;
    do {
        printf('Waiting for job to complete' . PHP_EOL);
        sleep(10);
        $job = $dlp->getDlpJob($job->getName());
        if ($job->getState() == JobState::DONE) {
            break;
        }
        $numOfAttempts--;
    } while ($numOfAttempts > 0);

    // 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.');
    }
}

Python

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import time
from typing import List

import google.cloud.dlp


def inspect_bigquery_send_to_scc(
    project: str,
    info_types: List[str],
    max_findings: int = 100,
) -> None:
    """
    Uses the Data Loss Prevention API to inspect public bigquery dataset
    and send the results to Google Security Command Center.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        info_types: A list of strings representing infoTypes to inspect for.
            A full list of infoType categories can be fetched from the API.
        max_findings: The maximum number of findings to report; 0 = no maximum
    """
    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries.
    info_types = [{"name": info_type} for info_type in info_types]

    # Construct the configuration dictionary.
    inspect_config = {
        "info_types": info_types,
        "min_likelihood": google.cloud.dlp_v2.Likelihood.UNLIKELY,
        "limits": {"max_findings_per_request": max_findings},
        "include_quote": True,
    }

    # Construct a Cloud Storage Options dictionary with the big query options.
    storage_config = {
        "big_query_options": {
            "table_reference": {
                "project_id": "bigquery-public-data",
                "dataset_id": "usa_names",
                "table_id": "usa_1910_current",
            }
        }
    }

    # Tell the API where to send a notification when the job is complete.
    actions = [{"publish_summary_to_cscc": {}}]

    # Construct the job definition.
    job = {
        "inspect_config": inspect_config,
        "storage_config": storage_config,
        "actions": actions,
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API.
    response = dlp.create_dlp_job(
        request={
            "parent": parent,
            "inspect_job": job,
        }
    )
    print(f"Inspection Job started : {response.name}")

    job_name = response.name

    # Waiting for a maximum of 15 minutes for the job to get complete.
    no_of_attempts = 30
    while no_of_attempts > 0:
        # Get the DLP job status.
        job = dlp.get_dlp_job(request={"name": job_name})
        # Check if the job has completed.
        if job.state == google.cloud.dlp_v2.DlpJob.JobState.DONE:
            break
        if job.state == google.cloud.dlp_v2.DlpJob.JobState.FAILED:
            print("Job Failed, Please check the configuration.")
            return

        # Sleep for a short duration before checking the job status again.
        time.sleep(30)
        no_of_attempts -= 1

    # Print out the results.
    print(f"Job name: {job.name}")
    result = job.inspect_details.result
    if result.info_type_stats:
        for stats in result.info_type_stats:
            print(f"Info type: {stats.info_type.name}")
            print(f"Count: {stats.count}")
    else:
        print("No findings.")

Contoh kode: memeriksa jenis Datastore

Contoh ini menunjukkan cara menggunakan DLP API untuk membuat tugas inspeksi yang memeriksa jenis Datastore dan mengirim temuan ke Security Command Center.

C#

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


using System.Collections.Generic;
using System.Linq;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using static Google.Cloud.Dlp.V2.InspectConfig.Types;

public class InspectDataStoreJobWithSCCIntegration
{
    public static DlpJob SendInspectDatastoreToSCC(
        string projectId,
        string kindName,
        string namespaceId,
        Likelihood minLikelihood = Likelihood.Unlikely,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Specify the Datastore entity to be inspected and construct the storage
        // config. The NamespaceId is to be used for partition entity and the datastore kind defining
        // a data set.
        var storageConfig = new StorageConfig
        {
            DatastoreOptions = new DatastoreOptions
            {
                Kind = new KindExpression { Name = kindName },
                PartitionId = new PartitionId
                {
                    NamespaceId = namespaceId,
                    ProjectId = projectId
                }
            }
        };

        // Specify the type of info to be inspected and construct the inspect config.
        var inspectConfig = new InspectConfig
        {
            InfoTypes =
            {
                infoTypes ?? new InfoType[]
                {
                    new InfoType { Name = "EMAIL_ADDRESS" },
                    new InfoType { Name = "PERSON_NAME" },
                    new InfoType { Name = "LOCATION" },
                    new InfoType { Name = "PHONE_NUMBER" }
                }
            },
            IncludeQuote = true,
            MinLikelihood = minLikelihood,
            Limits = new FindingLimits
            {
                MaxFindingsPerRequest = 100
            }
        };

        // Construct the SCC action which will be performed after inspecting the datastore.
        var actions = new Action[]
        {
            new Action
            {
                PublishSummaryToCscc = new Action.Types.PublishSummaryToCscc()
            }
        };

        // Construct the inspect job config using storage config, inspect config and action.
        var inspectJob = new InspectJobConfig
        {
            StorageConfig = storageConfig,
            InspectConfig = inspectConfig,
            Actions = { actions }
        };

        // Construct the request.
        var request = new CreateDlpJobRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            InspectJob = inspectJob
        };

        // Call the API.
        DlpJob response = dlp.CreateDlpJob(request);

        return response;
    }
}

Go

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// inspectDataStoreSendToScc inspects sensitive data in a Datastore
// and sends the results to Google Cloud Security Command Center (SCC).
func inspectDataStoreSendToScc(w io.Writer, projectID, datastoreNamespace, datastoreKind string) error {
	// projectID := "my-project-id"
	// datastoreNamespace := "your-datastore-namespace"
	// datastoreKind := "your-datastore-kind"

	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 Datastore entity to be inspected.
	partitionId := &dlppb.PartitionId{
		ProjectId:   projectID,
		NamespaceId: datastoreNamespace,
	}

	// kindExpr represents an expression specifying a kind or range of kinds for data inspection in DLP.
	kindExpression := &dlppb.KindExpression{
		Name: datastoreKind,
	}

	// Specify datastoreOptions so that It holds the configuration options for inspecting data in
	// Google Cloud Datastore.
	datastoreOptions := &dlppb.DatastoreOptions{
		PartitionId: partitionId,
		Kind:        kindExpression,
	}

	// Specify the storageConfig to represents the configuration settings for inspecting data
	// in different storage types, such as BigQuery and Cloud Storage.
	storageConfig := &dlppb.StorageConfig{
		Type: &dlppb.StorageConfig_DatastoreOptions{
			DatastoreOptions: datastoreOptions,
		},
	}

	// 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: "EMAIL_ADDRESS"},
		{Name: "PERSON_NAME"},
		{Name: "LOCATION"},
		{Name: "PHONE_NUMBER"},
	}

	// The minimum likelihood required before returning a match.
	minLikelihood := dlppb.Likelihood_UNLIKELY

	// The maximum number of findings to report (0 = server maximum).
	findingLimits := &dlppb.InspectConfig_FindingLimits{
		MaxFindingsPerItem: 100,
	}

	inspectConfig := &dlppb.InspectConfig{
		InfoTypes:     infoTypes,
		MinLikelihood: minLikelihood,
		Limits:        findingLimits,
		IncludeQuote:  true,
	}

	// Specify the action that is triggered when the job completes.
	action := &dlppb.Action{
		Action: &dlppb.Action_PublishSummaryToCscc_{
			PublishSummaryToCscc: &dlppb.Action_PublishSummaryToCscc{},
		},
	}

	// Configure the inspection 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,
		},
	}

	// Send the request.
	resp, err := client.CreateDlpJob(ctx, req)
	if err != nil {
		return err
	}

	// Print the result
	fmt.Fprintf(w, "Job created successfully: %v", resp.Name)
	return nil
}

Java

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


import com.google.cloud.dlp.v2.DlpServiceClient;
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.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.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PartitionId;
import com.google.privacy.dlp.v2.StorageConfig;
import java.io.IOException;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class InspectDatastoreSendToScc {

  private static final int TIMEOUT_MINUTES = 15;

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    // The Google Cloud project id to use as a parent resource.
    String projectId = "your-project-id";
    // The namespace specifier to be used for the partition entity.
    String datastoreNamespace = "your-datastore-namespace";
    // The datastore kind defining a data set.
    String datastoreKind = "your-datastore-kind";
    inspectDatastoreSendToScc(projectId, datastoreNamespace, datastoreKind);
  }

  // Creates a DLP Job to scan the sample data stored in a DataStore table and save its scan results
  // to Security Command Center.
  public static void inspectDatastoreSendToScc(
      String projectId, String datastoreNamespace, String datastoreKind)
      throws IOException, InterruptedException {
    // 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 dlpServiceClient = DlpServiceClient.create()) {

      // Specify the Datastore entity to be inspected.
      PartitionId partitionId =
          PartitionId.newBuilder()
              .setProjectId(projectId)
              .setNamespaceId(datastoreNamespace)
              .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.
      List<InfoType> infoTypes =
          Stream.of("EMAIL_ADDRESS", "PERSON_NAME", "LOCATION", "PHONE_NUMBER")
              .map(it -> InfoType.newBuilder().setName(it).build())
              .collect(Collectors.toList());

      // The minimum likelihood required before returning a match.
      Likelihood minLikelihood = Likelihood.UNLIKELY;

      // The maximum number of findings to report (0 = server maximum)
      InspectConfig.FindingLimits findingLimits =
          InspectConfig.FindingLimits.newBuilder().setMaxFindingsPerItem(100).build();

      // Specify how the content should be inspected.
      InspectConfig inspectConfig =
          InspectConfig.newBuilder()
              .addAllInfoTypes(infoTypes)
              .setIncludeQuote(true)
              .setMinLikelihood(minLikelihood)
              .setLimits(findingLimits)
              .build();

      // Specify the action that is triggered when the job completes.
      Action.PublishSummaryToCscc publishSummaryToCscc =
          Action.PublishSummaryToCscc.getDefaultInstance();
      Action action = Action.newBuilder().setPublishSummaryToCscc(publishSummaryToCscc).build();

      // Configure the inspection job we want the service to perform.
      InspectJobConfig inspectJobConfig =
          InspectJobConfig.newBuilder()
              .setInspectConfig(inspectConfig)
              .setStorageConfig(storageConfig)
              .addActions(action)
              .build();

      // Construct the job creation request to be sent by the client.
      CreateDlpJobRequest createDlpJobRequest =
          CreateDlpJobRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setInspectJob(inspectJobConfig)
              .build();

      // Send the job creation request and process the response.
      DlpJob response = dlpServiceClient.createDlpJob(createDlpJobRequest);
      // Get the current time.
      long startTime = System.currentTimeMillis();

      // Check if the job state is DONE.
      while (response.getState() != DlpJob.JobState.DONE) {
        // Sleep for 30 second.
        Thread.sleep(30000);

        // Get the updated job status.
        response = dlpServiceClient.getDlpJob(response.getName());

        // Check if the timeout duration has exceeded.
        long elapsedTime = System.currentTimeMillis() - startTime;
        if (TimeUnit.MILLISECONDS.toMinutes(elapsedTime) >= TIMEOUT_MINUTES) {
          System.out.printf("Job did not complete within %d minutes.%n", TIMEOUT_MINUTES);
          break;
        }
      }
      // Print the results.
      System.out.println("Job status: " + response.getState());
      System.out.println("Job name: " + response.getName());
      InspectDataSourceDetails.Result result = response.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());
      }
    }
  }
}

Node.js

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under.
// const projectId = "your-project-id";

// Datastore namespace
// const datastoreNamespace = 'datastore-namespace';

// Datastore kind
// const datastoreKind = 'datastore-kind';

async function inspectDatastoreSendToScc() {
  // Specify the storage configuration object with datastore.
  const storageConfig = {
    datastoreOptions: {
      kind: {
        name: datastoreKind,
      },
      partitionId: {
        projectId: projectId,
        namespaceId: datastoreNamespace,
      },
    },
  };

  // Construct the info types to look for in the datastore.
  const infoTypes = [
    {name: 'EMAIL_ADDRESS'},
    {name: 'PERSON_NAME'},
    {name: 'LOCATION'},
    {name: 'PHONE_NUMBER'},
  ];

  // Construct the inspection configuration.
  const inspectConfig = {
    infoTypes: infoTypes,
    minLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.UNLIKELY,
    limits: {
      maxFindingsPerItem: 100,
    },
    includeQuote: true,
  };

  // Specify the action that is triggered when the job completes
  const action = {
    publishSummaryToCscc: {enable: true},
  };

  // Configure the inspection job we want the service to perform.
  const inspectJobConfig = {
    inspectConfig: inspectConfig,
    storageConfig: storageConfig,
    actions: [action],
  };

  // Construct the job creation request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectJob: inspectJobConfig,
  };

  // Send the job creation request and process the response.
  const [jobsResponse] = await dlp.createDlpJob(request);
  const jobName = jobsResponse.name;

  // Waiting for a maximum of 15 minutes for the job to get complete.
  let job;
  let numOfAttempts = 30;
  while (numOfAttempts > 0) {
    // Fetch DLP Job status
    [job] = await dlp.getDlpJob({name: jobName});

    // Check if the job has completed.
    if (job.state === 'DONE') {
      break;
    }
    if (job.state === 'FAILED') {
      console.log('Job Failed, Please check the configuration.');
      return;
    }
    // Sleep for a short duration before checking the job status again.
    await new Promise(resolve => {
      setTimeout(() => resolve(), 30000);
    });
    numOfAttempts -= 1;
  }

  // Print out the results.
  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 inspectDatastoreSendToScc();

PHP

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectConfig\FindingLimits;
use Google\Cloud\Dlp\V2\StorageConfig;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\Action;
use Google\Cloud\Dlp\V2\Action\PublishSummaryToCscc;
use Google\Cloud\Dlp\V2\DatastoreOptions;
use Google\Cloud\Dlp\V2\InspectJobConfig;
use Google\Cloud\Dlp\V2\KindExpression;
use Google\Cloud\Dlp\V2\PartitionId;
use Google\Cloud\Dlp\V2\DlpJob\JobState;

/**
 * (DATASTORE) Send Cloud DLP scan results to Security Command Center.
 * Using Cloud Data Loss Prevention to scan specific Google Cloud resources and send data to Security Command Center.
 *
 * @param string $callingProjectId  The project ID to run the API call under.
 * @param string $kindName          Datastore kind name to be inspected.
 * @param string $namespaceId       Namespace Id to be inspected.
 */
function inspect_datastore_send_to_scc(
    string $callingProjectId,
    string $kindName,
    string $namespaceId
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    // Construct the items to be inspected.
    $datastoreOptions = (new DatastoreOptions())
        ->setKind((new KindExpression())
            ->setName($kindName))
        ->setPartitionId((new PartitionId())
            ->setNamespaceId($namespaceId)
            ->setProjectId($callingProjectId));

    $storageConfig = (new StorageConfig())
        ->setDatastoreOptions(($datastoreOptions));

    // Specify the type of info the inspection will look for.
    $infoTypes = [
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('PERSON_NAME'),
        (new InfoType())->setName('LOCATION'),
        (new InfoType())->setName('PHONE_NUMBER')
    ];

    // Specify how the content should be inspected.
    $inspectConfig = (new InspectConfig())
        ->setMinLikelihood(likelihood::UNLIKELY)
        ->setLimits((new FindingLimits())
            ->setMaxFindingsPerRequest(100))
        ->setInfoTypes($infoTypes)
        ->setIncludeQuote(true);

    // Specify the action that is triggered when the job completes.
    $action = (new Action())
        ->setPublishSummaryToCscc(new PublishSummaryToCscc());

    // Construct inspect job config to run.
    $inspectJobConfig = (new InspectJobConfig())
        ->setInspectConfig($inspectConfig)
        ->setStorageConfig($storageConfig)
        ->setActions([$action]);

    // Send the job creation request and process the response.
    $parent = "projects/$callingProjectId/locations/global";
    $job = $dlp->createDlpJob($parent, [
        'inspectJob' => $inspectJobConfig
    ]);

    $numOfAttempts = 10;
    do {
        printf('Waiting for job to complete' . PHP_EOL);
        sleep(10);
        $job = $dlp->getDlpJob($job->getName());
        if ($job->getState() == JobState::DONE) {
            break;
        }
        $numOfAttempts--;
    } while ($numOfAttempts > 0);

    // 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.');
    }
}

Python

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 

import time
from typing import List

import google.cloud.dlp


def inspect_datastore_send_to_scc(
    project: str,
    datastore_project: str,
    kind: str,
    info_types: List[str],
    namespace_id: str = None,
    max_findings: int = 100,
) -> None:
    """
    Uses the Data Loss Prevention API to inspect Datastore data and
    send the results to Google Security Command Center.
    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'.
        info_types: A list of strings representing infoTypes to inspect for.
            A full list of infoType categories can be fetched from the API.
        namespace_id: The namespace of the Datastore document, if applicable.
        max_findings: The maximum number of findings to report; 0 = no maximum

    """
    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries.
    info_types = [{"name": info_type} for info_type in info_types]

    # Construct the configuration dictionary.
    inspect_config = {
        "info_types": info_types,
        "min_likelihood": google.cloud.dlp_v2.Likelihood.UNLIKELY,
        "limits": {"max_findings_per_request": max_findings},
        "include_quote": True,
    }

    # Construct a cloud_storage_options dictionary with datastore options.
    storage_config = {
        "datastore_options": {
            "partition_id": {
                "project_id": datastore_project,
                "namespace_id": namespace_id,
            },
            "kind": {"name": kind},
        }
    }

    # Tell the API where to send a notification when the job is complete.
    actions = [{"publish_summary_to_cscc": {}}]

    # Construct the job definition.
    job = {
        "inspect_config": inspect_config,
        "storage_config": storage_config,
        "actions": actions,
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}"

    # Call the API
    response = dlp.create_dlp_job(
        request={
            "parent": parent,
            "inspect_job": job,
        }
    )
    print(f"Inspection Job started : {response.name}")

    job_name = response.name

    # Waiting for a maximum of 15 minutes for the job to get complete.
    no_of_attempts = 30
    while no_of_attempts > 0:
        # Get the DLP job status.
        job = dlp.get_dlp_job(request={"name": job_name})
        # Check if the job has completed.
        if job.state == google.cloud.dlp_v2.DlpJob.JobState.DONE:
            break
        if job.state == google.cloud.dlp_v2.DlpJob.JobState.FAILED:
            print("Job Failed, Please check the configuration.")
            return

        # Sleep for a short duration before checking the job status again.
        time.sleep(30)
        no_of_attempts -= 1

    # Print out the results.
    print(f"Job name: {job.name}")
    result = job.inspect_details.result
    if result.info_type_stats:
        for stats in result.info_type_stats:
            print(f"Info type: {stats.info_type.name}")
            print(f"Count: {stats.count}")
    else:
        print("No findings.")

Melihat hasil pemindaian Sensitive Data Protection di Security Command Center

Karena Anda menginstruksikan Perlindungan Data Sensitif untuk mengirim hasil tugas pemeriksaannya ke Security Command Center, kini Anda dapat melihat hasil tugas pemeriksaan di Security Command Center:

  1. Di konsol Google Cloud, buka halaman Temuan Security Command Center.

    Buka Temuan

  2. Pilih organisasi tempat Anda mengaktifkan Security Command Center.

  3. Di kolom Query editor, masukkan perintah berikut untuk mengkueri temuan dari Perlindungan Data Sensitif.

    state="ACTIVE"
AND NOT mute="MUTED"
AND (parent_display_name="Sensitive Data Protection" OR parent_display_name="Cloud Data Loss Prevention")

    Untuk mengetahui informasi editor kueri selengkapnya, lihat Mengedit kueri temuan di konsol Google Cloud.

    Jika ada temuan yang dikirim dari Perlindungan Data Sensitif, temuan tersebut akan muncul di daftar temuan. Daftar ini mencakup semua temuan dari Perlindungan Data Sensitif, yang dapat mencakup temuan dari tugas pemeriksaan dan operasi penemuan (pembuatan profil data).

Petunjuk yang diberikan dalam panduan ini hanya mengaktifkan beberapa detektor bawaan Perlindungan Data Sensitif.

Pembersihan

Agar tidak menimbulkan tagihan ke akun Google Cloud Anda untuk resource yang digunakan dalam topik ini:

Menghapus project

Cara termudah untuk menghilangkan penagihan adalah dengan menghapus project yang Anda buat sembari mengikuti petunjuk yang diberikan dalam topik ini.

  1. In the Google Cloud console, go to the Manage resources page.

    Go to Manage resources

  2. In the project list, select the project that you want to delete, and then click Delete.
  3. In the dialog, type the project ID, and then click Shut down to delete the project.

Jika Anda menghapus project menggunakan metode ini, tugas Sensitive Data Protection dan bucket Cloud Storage yang Anda buat juga akan dihapus. Anda tidak perlu mengikuti petunjuk di bagian berikut.

Menghapus tugas Sensitive Data Protection

Jika Anda memindai data Anda sendiri, Anda hanya perlu menghapus tugas inspeksi yang Anda buat:

  1. Buka API Explorer di halaman referensi untuk metode dlpJobs.delete dengan mengklik tombol berikut:

    Membuka API Explorer

  2. Di kotak name, ketik nama tugas dari respons JSON ke permintaan pemindaian, yang memiliki bentuk berikut: 
    projects/PROJECT_ID/dlpJobs/JOB_ID
     ID tugas dalam bentuk i-1234567890123456789.

Jika Anda membuat tugas pemeriksaan tambahan atau ingin memastikan bahwa Anda telah berhasil menghapus tugas, Anda dapat mencantumkan semua tugas yang ada:

  1. Buka API Explorer di halaman referensi untuk metode dlpJobs.list dengan mengklik tombol berikut:

    Membuka API Explorer

  2. Di kotak parent, ketik ID project dalam bentuk berikut: 
    projects/PROJECT_ID
  3. Klik Jalankan.

Jika tidak ada tugas yang tercantum dalam respons, berarti Anda telah menghapus semua tugas. Jika tugas tercantum dalam respons, ulangi prosedur penghapusan untuk tugas tersebut.

Menghapus bucket Cloud Storage

Jika Anda membuat bucket Cloud Storage baru untuk menyimpan data sampel, hapus bucket tersebut:

  1. Buka browser Cloud Storage.

    Buka Cloud Storage

  2. Di browser Cloud Storage, pilih kotak centang di samping nama bucket yang Anda buat, lalu klik Hapus.

Langkah selanjutnya