自动扫描操作系统软件包

在本文档中,您将了解如何启用 Container Scanning API、将映像推送到 Artifact Registry,以及查看在映像中发现的漏洞列表。

Artifact Analysis 可为 Artifact Registry 和 Container Registry(已废弃)中的容器映像提供漏洞信息。元数据存储为备注。Container Analysis 会为与映像相关联的备注的每个实例创建一个发生实例。如需了解详情,请参阅概览价格文档。

启用此 API 还会在 Artifact Registry 中启用语言包扫描。请参阅支持的软件包类型

准备工作

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Google Cloud project.

  4. Enable the Artifact Registry and Container Scanning APIs.

    Enable the APIs

  5. Install the Google Cloud CLI.
  6. To initialize the gcloud CLI, run the following command:

    gcloud init
  7. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  8. Make sure that billing is enabled for your Google Cloud project.

  9. Enable the Artifact Registry and Container Scanning APIs.

    Enable the APIs

  10. Install the Google Cloud CLI.
  11. To initialize the gcloud CLI, run the following command:

    gcloud init
  12. 在 Artifact Registry 中创建一个 Docker 仓库,并将容器映像推送到该仓库。如果您不熟悉 Artifact Registry,请参阅 Docker 快速入门

Artifact Analysis 不会自动扫描现有映像。如需扫描现有映像,必须再次推送。

查看映像漏洞

Artifact Analysis 会在有新映像上传到 Artifact Registry 时扫描这些映像。此扫描可提取有关容器中系统软件包的信息。

您可以使用 Google Cloud 控制台、Google Cloud CLI 或 Container Analysis API 在注册库中查看映像的漏洞事件。如果某个映像存在漏洞,您就可以获取详细信息。

Artifact Analysis 只会更新过去 30 天内推送或拉取的映像的元数据。Artifact Analysis 会归档超过 30 天的元数据。如需重新扫描包含归档元数据的映像,请拉取该映像。刷新元数据最多可能需要 24 小时。

在 Google Cloud 控制台中查看出现情况

如需查看映像中的漏洞,请执行以下操作:

  1. 获取代码库列表。

    打开“代码库”页面

  2. 在代码库列表中,点击一个代码库。

  3. 在图片列表中,点击图片名称。

    每个映像摘要的漏洞总数将显示在漏洞列中。

    存在漏洞的映像的屏幕截图

  4. 如需查看映像的漏洞列表,请点击漏洞列中的链接。

    扫描结果部分会显示扫描的软件包类型、漏洞总数、可修复的漏洞、无法修复的漏洞以及有效的严重级别的摘要。

    显示漏洞、修复程序和有效严重性的“扫描结果”部分的屏幕截图

    漏洞表会列出每个发现的漏洞的常见漏洞和披露 (CVE) 名称、实际严重级别、通用漏洞评分系统 (CVSS) 评分、修复程序(如果有)、包含漏洞的软件包的名称和软件包类型。

    您可以过滤和排序这些文件,以按文件扩展名查看特定文件、目录或文件类型。

    Google Cloud 控制台最多会在此表格中显示 1,200 个漏洞。如果您的映像有超过 1200 个漏洞,您必须使用 gcloud 或 API 才能查看完整列表。

  5. 如需详细了解特定 CVE,请点击 CVE 名称。

  6. 如需查看漏洞出现详情(例如版本号和受影响的位置),请点击包含漏洞名称的行中的查看查看已修复。对于尚无修复程序的漏洞,链接文字为查看;对于已应用修复程序的漏洞,链接文字为查看已修复

使用 gcloud 查看出现情况

如需查看映像的发生实例,请使用以下命令

Artifact Registry

gcloud artifacts docker images list --show-occurrences \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

其中:

  • LOCATION 是代码库的单区域或多区域位置
  • PROJECT_ID 是您的 Google Cloud 项目 ID
  • REPOSITORY 是存储了映像的代码库的名称。
  • IMAGE_ID 是代码库中的映像名称。您无法使用此命令指定映像标记。

默认情况下,该命令会返回最近的 10 张图片。如需显示不同数量的图片,请使用 --show-occurrences-from 标志。例如,以下命令会返回最近 25 张图片。

gcloud artifacts docker images list --show-occurrences-from=25 \
us-central1-docker.pkg.dev/my-project/my-repo/my-image

Container Registry

gcloud beta container images list-tags \
HOSTNAME/PROJECT_ID/IMAGE_ID

其中:

  • HOSTNAME 是多区域主机名:
    • gcr.io
    • asia.gcr.io
    • eu.gcr.io
    • us.gcr.io
  • PROJECT_ID 是包含相应映像的项目的 ID。
  • IMAGE_ID 是您要查看其漏洞的映像的 ID。您无法使用此命令指定映像标记。

默认情况下,该命令会返回最近的 10 张图片。如需显示不同数量的图片,请使用 --show-occurrences-from 标志。例如,以下命令会返回最近 25 张图片。

gcloud beta container images list-tags --show-occurrences-from=25 \
gcr.io/my-project/my-image

如需查看某一映像标记或图层的漏洞,请使用以下命令

Artifact Registry

gcloud artifacts docker images describe \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID:TAG \
--show-package-vulnerability

gcloud artifacts docker images describe \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID@sha256:HASH \
--show-package-vulnerability

其中:

  • LOCATION 是代码库的单区域或多区域位置
  • PROJECT_ID 是您的 Google Cloud 项目 ID
  • REPOSITORY 是存储了映像的代码库的名称。
  • IMAGE_ID 是代码库中的映像名称。
  • TAG 是您想要获取其相关信息的图片标记。
  • HASH 是映像摘要。

Container Registry

gcloud beta container images describe HOSTNAME/PROJECT_ID/IMAGE_ID@sha256:HASH \
--show-package-vulnerability

其中:

  • HOSTNAME 是多区域主机名:
    • gcr.io
    • asia.gcr.io
    • eu.gcr.io
    • us.gcr.io
  • PROJECT_ID 是包含相应映像的项目的 ID。
  • IMAGE_ID 是您要查看其漏洞的映像的 ID。
  • HASH 是映像摘要。

如需过滤漏洞发生实例,请使用以下命令

Artifact Registry

gcloud artifacts docker images list --show-occurrences \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID --occurrence-filter=FILTER_EXPRESSION

其中:

  • LOCATION 是代码库的单区域或多区域位置
  • PROJECT_ID 是您的 Google Cloud 项目 ID
  • REPOSITORY 是存储了映像的代码库的名称。
  • IMAGE_ID 是代码库中的映像名称。
  • FILTER_EXPRESSION 是一个示例过滤条件表达式,其格式请参阅过滤漏洞事件

Container Registry

gcloud beta container images list-tags \
HOSTNAME/PROJECT_ID/IMAGE_ID --occurrence-filter=FILTER_EXPRESSION

其中:

  • HOSTNAME 是多区域主机名:
    • gcr.io
    • asia.gcr.io
    • eu.gcr.io
    • us.gcr.io
  • PROJECT_ID 是包含相应映像的项目的 ID。
  • IMAGE_ID 是您要查看其漏洞发生实例的映像的 ID。
  • FILTER_EXPRESSION 是一个示例过滤条件表达式,其格式请参阅过滤漏洞事件

使用 API 或代码查看出现情况

如需查看映像的发生实例,请使用相应的代码段。这些代码段指定了 Container Registry 中映像的网址。如果您使用的是 Artifact Registry,请使用以下格式的网址指定映像:

LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

API

使用 cURL

如需获取项目中发生实例的列表,请使用以下命令:

 curl -X GET -H "Content-Type: application/json" -H \
    "Authorization: Bearer $(gcloud auth print-access-token)" \
    https://containeranalysis.googleapis.com/v1/projects/PROJECT_ID/occurrences

如需获取项目中漏洞的汇总,请使用以下命令:

 curl -X GET -H "Content-Type: application/json" -H \
    "Authorization: Bearer $(gcloud auth print-access-token)" \
    https://containeranalysis.googleapis.com/v1/projects/PROJECT_ID/occurrences:vulnerabilitySummary

如需获取特定发生实例的详细信息,请执行以下操作:

 curl -X GET -H "Content-Type: application/json" -H \
    "Authorization: Bearer $(gcloud auth print-access-token)" \
    https://containeranalysis.googleapis.com/v1/projects/PROJECT_ID/occurrences/OCCURRENCE_ID

Java

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Java API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

import com.google.cloud.devtools.containeranalysis.v1.ContainerAnalysisClient;
import io.grafeas.v1.GrafeasClient;
import io.grafeas.v1.Occurrence;
import io.grafeas.v1.ProjectName;
import java.io.IOException;
import java.lang.InterruptedException;

public class OccurrencesForImage {
  // Retrieves all the Occurrences associated with a specified image
  // Here, all Occurrences are simply printed and counted
  public static int getOccurrencesForImage(String resourceUrl, String projectId)
      throws IOException, InterruptedException {
    // String resourceUrl = "https://gcr.io/project/image@sha256:123";
    // String projectId = "my-project-id";
    final String projectName = ProjectName.format(projectId);
    final String filterStr = String.format("resourceUrl=\"%s\"", resourceUrl);

    // Initialize client that will be used to send requests. After completing all of your requests, 
    // call the "close" method on the client to safely clean up any remaining background resources.
    GrafeasClient client = ContainerAnalysisClient.create().getGrafeasClient();
    int i = 0;
    for (Occurrence o : client.listOccurrences(projectName, filterStr).iterateAll()) {
      // Write custom code to process each Occurrence here
      System.out.println(o.getName());
      i = i + 1;
    }
    return i;
  }
}

Go

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Go API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证


import (
	"context"
	"fmt"
	"io"

	containeranalysis "cloud.google.com/go/containeranalysis/apiv1"
	"google.golang.org/api/iterator"
	grafeaspb "google.golang.org/genproto/googleapis/grafeas/v1"
)

// getOccurrencesForImage retrieves all the Occurrences associated with a specified image.
// Here, all Occurrences are simply printed and counted.
func getOccurrencesForImage(w io.Writer, resourceURL, projectID string) (int, error) {
	// Use this style of URL when you use Google Container Registry.
	// resourceURL := "https://gcr.io/my-project/my-repo/my-image"
	// Use this style of URL when you use Google Artifact Registry.
	// resourceURL := "https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image"
	ctx := context.Background()
	client, err := containeranalysis.NewClient(ctx)
	if err != nil {
		return -1, fmt.Errorf("NewClient: %w", err)
	}
	defer client.Close()

	req := &grafeaspb.ListOccurrencesRequest{
		Parent: fmt.Sprintf("projects/%s", projectID),
		Filter: fmt.Sprintf("resourceUrl=%q", resourceURL),
	}
	it := client.GetGrafeasClient().ListOccurrences(ctx, req)
	count := 0
	for {
		occ, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			return -1, fmt.Errorf("occurrence iteration error: %w", err)
		}
		// Write custom code to process each Occurrence here.
		fmt.Fprintln(w, occ)
		count = count + 1
	}
	return count, nil
}

Node.js

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Node.js API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

/**
 * TODO(developer): Uncomment these variables before running the sample
 */
// const projectId = 'your-project-id', // Your GCP Project ID
// If you are using Google Container Registry
// const imageUrl = 'https://gcr.io/my-project/my-repo/my-image@sha256:123' // Image to attach metadata to
// If you are using Google Artifact Registry
// const imageUrl = 'https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image@sha256:123' // Image to attach metadata to

// Import the library and create a client
const {ContainerAnalysisClient} = require('@google-cloud/containeranalysis');
const client = new ContainerAnalysisClient();

const formattedParent = client.getGrafeasClient().projectPath(projectId);

// Retrieves all the Occurrences associated with a specified image
const [occurrences] = await client.getGrafeasClient().listOccurrences({
  parent: formattedParent,
  filter: `resourceUrl = "${imageUrl}"`,
});

if (occurrences.length) {
  console.log(`Occurrences for ${imageUrl}`);
  occurrences.forEach(occurrence => {
    console.log(`${occurrence.name}:`);
  });
} else {
  console.log('No occurrences found.');
}

Ruby

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Ruby API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

# resource_url = "The URL of the resource associated with the occurrence."
#                # e.g. https://gcr.io/project/image@sha256:123"
# project_id   = "The Google Cloud project ID of the occurrences to retrieve"

require "google/cloud/container_analysis"

# Initialize the client
client = Google::Cloud::ContainerAnalysis.container_analysis.grafeas_client

parent = client.project_path project: project_id
filter = "resourceUrl = \"#{resource_url}\""
count = 0
client.list_occurrences(parent: parent, filter: filter).each do |occurrence|
  # Process occurrence here
  puts occurrence
  count += 1
end
puts "Found #{count} occurrences"

Python

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Python API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

from google.cloud.devtools import containeranalysis_v1


def get_occurrences_for_image(resource_url: str, project_id: str) -> int:
    """Retrieves all the occurrences associated with a specified image.
    Here, all occurrences are simply printed and counted."""
    # resource_url = 'https://gcr.io/my-project/my-image@sha256:123'
    # project_id = 'my-gcp-project'

    filter_str = f'resourceUrl="{resource_url}"'
    client = containeranalysis_v1.ContainerAnalysisClient()
    grafeas_client = client.get_grafeas_client()
    project_name = f"projects/{project_id}"

    response = grafeas_client.list_occurrences(parent=project_name, filter=filter_str)
    count = 0
    for o in response:
        # do something with the retrieved occurrence
        # in this sample, we will simply count each one
        count += 1
    return count

在 Cloud Build 中查看出现情况

如果您使用的是 Cloud Build,还可以在 Google Cloud 控制台的安全分析侧边栏中查看映像漏洞。

安全性数据分析侧边栏提供了存储在 Artifact Registry 中的工件的构建安全信息的概览。如需详细了解侧边栏以及如何使用 Cloud Build 帮助保护软件供应链,请参阅查看构建安全数据分析

过滤发生实例

您可以在 gcloud 命令和 Artifact Analysis API 中使用过滤条件字符串,以便在查看发生实例之前对其进行过滤。以下部分介绍了支持的搜索过滤条件。

查看扫描结果实例

当某个映像最初被推送到 Container Registry 时,该服务会创建一个扫描结果实例,其中包含有关容器映像初始扫描的信息。

如需检索映像的扫描结果实例,请使用以下过滤条件表达式:

kind="DISCOVERY" AND resourceUrl="RESOURCE_URL"

以下代码段展示了如何使用过滤条件表达式来查看映像的扫描结果实例。这些代码段指定了 Container Registry 中映像的网址。如果您使用的是 Artifact Registry,请使用以下格式的网址指定映像:

LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

gcloud

如需查看映像的扫描结果实例,请使用以下命令

在这种情况下,该表达式不会直接在命令中使用,而是以参数的形式传递相同的信息:

Artifact Registry:

gcloud artifacts docker images list --show-occurrences \
--occurrence-filter='kind="DISCOVERY"' --format=json \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

Container Registry:

gcloud beta container images list-tags \
--occurrence-filter='kind="DISCOVERY"' --format=json HOSTNAME/PROJECT_ID/IMAGE_ID

API

如需检索发现事件,您的过滤条件表达式必须采用网址编码并嵌入 GET 请求中,具体如下所示:

GET https://containeranalysis.googleapis.com/v1/projects/PROJECT_ID/occurrences?filter=kind%3D%22DISCOVERY%22%20AND%20resourceUrl%3D%22ENCODED_RESOURCE_URL%22

如需了解详情,请参阅 projects.occurrences.get API 端点。

Java

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Java API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

import com.google.cloud.devtools.containeranalysis.v1.ContainerAnalysisClient;
import io.grafeas.v1.GrafeasClient;
import io.grafeas.v1.Occurrence;
import io.grafeas.v1.ProjectName;
import java.io.IOException;
import java.lang.InterruptedException;

public class GetDiscoveryInfo {
  // Retrieves and prints the Discovery Occurrence created for a specified image
  // The Discovery Occurrence contains information about the initial scan on the image
  public static void getDiscoveryInfo(String resourceUrl, String projectId) 
      throws IOException, InterruptedException {
    // String resourceUrl = "https://gcr.io/project/image@sha256:123";
    // String projectId = "my-project-id";
    String filterStr = "kind=\"DISCOVERY\" AND resourceUrl=\"" + resourceUrl + "\"";
    final String projectName = ProjectName.format(projectId);

    // Initialize client that will be used to send requests. After completing all of your requests, 
    // call the "close" method on the client to safely clean up any remaining background resources.
    GrafeasClient client = ContainerAnalysisClient.create().getGrafeasClient();
    for (Occurrence o : client.listOccurrences(projectName, filterStr).iterateAll()) {
      System.out.println(o);
    }
  }
}

Go

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Go API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证


import (
	"context"
	"fmt"
	"io"

	containeranalysis "cloud.google.com/go/containeranalysis/apiv1"
	"google.golang.org/api/iterator"
	grafeaspb "google.golang.org/genproto/googleapis/grafeas/v1"
)

// getDiscoveryInfo retrieves and prints the Discovery Occurrence created for a specified image.
// The Discovery Occurrence contains information about the initial scan on the image.
func getDiscoveryInfo(w io.Writer, resourceURL, projectID string) error {
	// Use this style of URL when you use Google Container Registry.
	// resourceURL := "https://gcr.io/my-project/my-repo/my-image"
	// Use this style of URL when you use Google Artifact Registry.
	// resourceURL := "https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image"
	ctx := context.Background()
	client, err := containeranalysis.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("NewClient: %w", err)
	}
	defer client.Close()

	req := &grafeaspb.ListOccurrencesRequest{
		Parent: fmt.Sprintf("projects/%s", projectID),
		Filter: fmt.Sprintf(`kind="DISCOVERY" AND resourceUrl=%q`, resourceURL),
	}
	it := client.GetGrafeasClient().ListOccurrences(ctx, req)
	for {
		occ, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			return fmt.Errorf("occurrence iteration error: %w", err)
		}
		fmt.Fprintln(w, occ)
	}
	return nil
}

Node.js

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Node.js API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

/**
 * TODO(developer): Uncomment these variables before running the sample
 */
// const projectId = 'your-project-id', // Your GCP Project ID
// If you are using Google Container Registry
// const imageUrl = 'https://gcr.io/my-project/my-repo/my-image:123' // Image to attach metadata to
// If you are using Google Artifact Registry
// const imageUrl = 'https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image:123' // Image to attach metadata to

// Import the library and create a client
const {ContainerAnalysisClient} = require('@google-cloud/containeranalysis');
const client = new ContainerAnalysisClient();

const formattedParent = client.getGrafeasClient().projectPath(projectId);
// Retrieves and prints the Discovery Occurrence created for a specified image
// The Discovery Occurrence contains information about the initial scan on the image
const [occurrences] = await client.getGrafeasClient().listOccurrences({
  parent: formattedParent,
  filter: `kind = "DISCOVERY" AND resourceUrl = "${imageUrl}"`,
});

if (occurrences.length > 0) {
  console.log(`Discovery Occurrences for ${imageUrl}`);
  occurrences.forEach(occurrence => {
    console.log(`${occurrence.name}:`);
  });
} else {
  console.log('No occurrences found.');
}

Ruby

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Ruby API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

# resource_url = "The URL of the resource associated with the occurrence."
#                # e.g. https://gcr.io/project/image@sha256:123
# project_id   = "The Google Cloud project ID of the occurrences to retrieve"

require "google/cloud/container_analysis"

# Initialize the client
client = Google::Cloud::ContainerAnalysis.container_analysis.grafeas_client

parent = client.project_path project: project_id
filter = "kind = \"DISCOVERY\" AND resourceUrl = \"#{resource_url}\""
client.list_occurrences(parent: parent, filter: filter).each do |occurrence|
  # Process discovery occurrence here
  puts occurrence
end

Python

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Python API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

from google.cloud.devtools import containeranalysis_v1


def get_discovery_info(resource_url: str, project_id: str) -> None:
    """Retrieves and prints the discovery occurrence created for a specified
    image. The discovery occurrence contains information about the initial
    scan on the image."""
    # resource_url = 'https://gcr.io/my-project/my-image@sha256:123'
    # project_id = 'my-gcp-project'

    filter_str = f'kind="DISCOVERY" AND resourceUrl="{resource_url}"'
    client = containeranalysis_v1.ContainerAnalysisClient()
    grafeas_client = client.get_grafeas_client()
    project_name = f"projects/{project_id}"
    response = grafeas_client.list_occurrences(parent=project_name, filter_=filter_str)
    for occ in response:
        print(occ)

查看漏洞发生实例

如需查看特定映像的漏洞发生实例,请使用过滤条件表达式创建查询:

kind="VULNERABILITY" AND resourceUrl="RESOURCE_URL"

以下代码段展示了如何检索映像的漏洞发生实例列表。这些代码段指定了 Container Registry 中映像的网址。如果您使用的是 Artifact Registry,请使用以下格式的网址指定映像:

LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

gcloud

如需查看映像的漏洞发生实例,请使用以下命令

在这种情况下,该表达式不会直接在命令中使用,而是以参数的形式传递相同的信息:

Artifact Registry

gcloud artifacts docker images list --show-occurrences \
--occurrence-filter='kind="VULNERABILITY"' --format=json \
LOCATION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_ID

Container Registry

gcloud beta container images list-tags \
--occurrence-filter='kind="VULNERABILITY"' --format=json HOSTNAME/PROJECT_ID/IMAGE_ID

API

资源网址必须采用网址编码并嵌入 GET 请求中,具体如下所示:

GET https://containeranalysis.googleapis.com/v1/projects/PROJECT_ID/occurrences?filter=kind%3D%22VULNERABILITY%22%20AND%20resourceUrl%3D%22ENCODED_RESOURCE_URL%22

如需了解详情,请参阅 projects.occurrences.get API 端点。

Java

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Java API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

import com.google.cloud.devtools.containeranalysis.v1.ContainerAnalysisClient;
import io.grafeas.v1.GrafeasClient;
import io.grafeas.v1.Occurrence;
import io.grafeas.v1.ProjectName;
import java.io.IOException;
import java.util.LinkedList;
import java.util.List;

public class VulnerabilityOccurrencesForImage {
  // Retrieve a list of vulnerability occurrences assoviated with a resource
  public static List<Occurrence> findVulnerabilityOccurrencesForImage(String resourceUrl, 
      String projectId) throws IOException {
    // String resourceUrl = "https://gcr.io/project/image@sha256:123";
    // String projectId = "my-project-id";
    final String projectName = ProjectName.format(projectId);
    String filterStr = String.format("kind=\"VULNERABILITY\" AND resourceUrl=\"%s\"", resourceUrl);

    // Initialize client that will be used to send requests. After completing all of your requests, 
    // call the "close" method on the client to safely clean up any remaining background resources.
    GrafeasClient client = ContainerAnalysisClient.create().getGrafeasClient();
    LinkedList<Occurrence> vulnerabilitylist = new LinkedList<Occurrence>();
    for (Occurrence o : client.listOccurrences(projectName, filterStr).iterateAll()) {
      vulnerabilitylist.add(o);
    }
    return vulnerabilitylist;
  }
}

Go

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Go API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证


import (
	"context"
	"fmt"

	containeranalysis "cloud.google.com/go/containeranalysis/apiv1"
	"google.golang.org/api/iterator"
	grafeaspb "google.golang.org/genproto/googleapis/grafeas/v1"
)

// findVulnerabilityOccurrencesForImage retrieves all vulnerability Occurrences associated with a resource.
func findVulnerabilityOccurrencesForImage(resourceURL, projectID string) ([]*grafeaspb.Occurrence, error) {
	// Use this style of URL when you use Google Container Registry.
	// resourceURL := "https://gcr.io/my-project/my-repo/my-image"
	// Use this style of URL when you use Google Artifact Registry.
	// resourceURL := "https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image"
	ctx := context.Background()
	client, err := containeranalysis.NewClient(ctx)
	if err != nil {
		return nil, fmt.Errorf("NewClient: %w", err)
	}
	defer client.Close()

	req := &grafeaspb.ListOccurrencesRequest{
		Parent: fmt.Sprintf("projects/%s", projectID),
		Filter: fmt.Sprintf("resourceUrl = %q kind = %q", resourceURL, "VULNERABILITY"),
	}

	var occurrenceList []*grafeaspb.Occurrence
	it := client.GetGrafeasClient().ListOccurrences(ctx, req)
	for {
		occ, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			return nil, fmt.Errorf("occurrence iteration error: %w", err)
		}
		occurrenceList = append(occurrenceList, occ)
	}

	return occurrenceList, nil
}

Node.js

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Node.js API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

/**
 * TODO(developer): Uncomment these variables before running the sample
 */
// const projectId = 'your-project-id', // Your GCP Project ID
// If you are using Google Container Registry
// const imageUrl = 'https://gcr.io/my-project/my-repo/my-image:123' // Image to attach metadata to
// If you are using Google Artifact Registry
// const imageUrl = 'https://LOCATION-docker.pkg.dev/my-project/my-repo/my-image:123' // Image to attach metadata to

// Import the library and create a client
const {ContainerAnalysisClient} = require('@google-cloud/containeranalysis');
const client = new ContainerAnalysisClient();

const formattedParent = client.getGrafeasClient().projectPath(projectId);

// Retrieve a list of vulnerability occurrences assoviated with a resource
const [occurrences] = await client.getGrafeasClient().listOccurrences({
  parent: formattedParent,
  filter: `kind = "VULNERABILITY" AND resourceUrl = "${imageUrl}"`,
});

if (occurrences.length) {
  console.log(`All Vulnerabilities for ${imageUrl}`);
  occurrences.forEach(occurrence => {
    console.log(`${occurrence.name}:`);
  });
} else {
  console.log('No occurrences found.');
}

Ruby

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Ruby API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

# resource_url = "The URL of the resource associated with the occurrence
#                e.g. https://gcr.io/project/image@sha256:123"
# project_id   = "The Google Cloud project ID of the vulnerabilities to find"

require "google/cloud/container_analysis"

# Initialize the client
client = Google::Cloud::ContainerAnalysis.container_analysis.grafeas_client

parent = client.project_path project: project_id
filter = "resourceUrl = \"#{resource_url}\" AND kind = \"VULNERABILITY\""
client.list_occurrences parent: parent, filter: filter

Python

如需了解如何安装和使用工件分析的客户端库,请参阅 Artifact Analysis 客户端库。 如需了解详情,请参阅 Artifact Analysis Python API 参考文档

如需向 Artifact Analysis 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证

from typing import List

from google.cloud.devtools import containeranalysis_v1
from grafeas.grafeas_v1 import types


def find_vulnerabilities_for_image(
    resource_url: str, project_id: str
) -> List[types.grafeas.Occurrence]:
    """ "Retrieves all vulnerability occurrences associated with a resource."""
    # resource_url = 'https://gcr.io/my-project/my-image@sha256:123'
    # project_id = 'my-gcp-project'

    client = containeranalysis_v1.ContainerAnalysisClient()
    grafeas_client = client.get_grafeas_client()
    project_name = f"projects/{project_id}"

    filter_str = 'kind="VULNERABILITY" AND resourceUrl="{}"'.format(resource_url)
    return list(grafeas_client.list_occurrences(parent=project_name, filter=filter_str))

查看特定类型的发生实例

在前面的两个示例中,过滤条件表达式之间的唯一区别是标识发生实例类型的 kind 值。使用此字段可将发生实例列表限制为特定类型,例如漏洞或部署。

如需检查特定映像的发生实例,请使用以下过滤条件表达式:

kind="NOTE_KIND" AND resourceUrl="RESOURCE_URL"

其中:

  • NOTE_KIND 是备注的种类
    • 例如,使用 DISCOVERY 种类可列出扫描结果实例。 这些发生实例是在映像最初被推送到 Container Registry 时为其创建的。
    • 如需列出漏洞发生实例,请使用 VULNERABILITY 种类。
  • RESOURCE_URL 是图片 https://HOSTNAME/PROJECT_ID/IMAGE_ID@sha256:HASH 的完整网址

用于在多个映像中检索特定种类发生实例的过滤条件表达式如下:

kind="NOTE_KIND" AND has_prefix(resourceUrl, "RESOURCE_URL_PREFIX")

其中:

  • RESOURCE_URL_PREFIX 是某些映像的网址前缀
    • 如需列出映像的所有版本,请使用以下网址前缀:https://HOSTNAME/PROJECT_ID/IMAGE_ID@
    • 如需列出项目中的所有映像,请使用以下网址前缀:https://HOSTNAME/PROJECT_ID/

查看与特定备注相关联的图片

您可以检索与特定备注 ID 相关联的资源列表。例如,您可以列出具有特定 CVE 漏洞的映像。

如需列出项目中与特定备注相关联的所有映像,请使用以下过滤条件表达式:

noteProjectId="PROVIDER_PROJECT_ID" AND noteId="NOTE_ID"

如需检查特定备注的特定映像,请使用以下过滤条件表达式:

resourceUrl="RESOURCE_URL" AND noteProjectId="PROVIDER_PROJECT_ID" \
    AND noteId="NOTE_ID"

其中:

  • PROVIDER_PROJECT_ID 是提供商项目的 ID。例如,goog-vulnz 提供默认的漏洞分析。
  • NOTE_ID 是备注的 ID。安全相关备注的格式通常为 CVE-2019-12345
  • RESOURCE_URL 是图片 https://HOSTNAME/PROJECT_ID/IMAGE_ID@sha256:HASH 的完整网址

例如,如需检查经 Google 分析具有 CVE-2017-16231 发生实例的所有映像,请使用以下过滤条件表达式:

noteProjectId="goog-vulnz" AND noteId="CVE-2017-16231"

后续步骤