Table of contents

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Overview

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Here we will explain the steps to build the iPRO Camera SDK app using the Azure IoT Edge container and check its operation. Also, in this tutorial, the SDK installation directory is described as ${SDK_DIR}.

Operation confirmation procedure

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Create a new IoT Edge Solution on Visual Studio Code

The following describes the case where the sample app to be referenced is skeleton_sample_app for the C version, additional_info_sample_app for the Python version, and test_app for the Edge Solution to be created. Please note that the Edge Solution name must be in all lowercase letters. Please see below for details.
https://docs.docker.com/reference/cli/docker/image/tag/

Description of C version/Python version application

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Enter the information for the container registry to which you want to push the created image.

Log in to Azure portal(Cloud Computing Services | Microsoft Azure) and select the container registry you want to target. The screen below is an example.

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Display "Settings" - "Access Keys" from the left menu.

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Based on the information displayed, enter the following:

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When using the container registry operated by i-PRO to build a development environment, please use the values in the table below for each item in the explanation below. If you want to prepare a container registry yourself, please refer to the documentation of the container registry you are using to obtain the values.

Enter the following based on the information you obtained.

• ${SDK_DIR}\src\adamapp\test_app\container\deployment.template.json
  Enter “registryCredentials” in the above file as follows. "Container Registry Name" is the "Registry Name" of Azure Portal in lower case (same as the string before .azurecr.io in "Login Server").

  Code Block"registryCredentials": { "[container registry name]":

  Code Block
  "registryCredentials": { "[container registry name]": { "username": "$CONTAINER_REGISTRY_USERNAME_[container registry name]", "password": "$CONTAINER_REGISTRY_PASSWORD_[container registry name]", "address": "[login server]" } }

  For example, if in the container registry name is “iprocv5xcontainerregistry” and the container registry login server is “iprocv5xcontainerregistry.azurecr.io”, it will case of a container registry operated by i-PRO, it would be as follows.

  Image Removed

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•  ${SDK_DIR}\src\adamapp\test_app\container\modules\test_app\module.json
  Enter “repository” in the above file as follows.

  Code Block
  "repository": "[login server]/[repository name]/test_app"

  If the For example, if the container registry login server is "iprocv5xcontainerregistry“iprocamsdk.azurecr.io"io” and the repository name is “dev/company-a”, it will be as follows.

  Image RemovedImage Added

• ${SDK_DIR}\src\adamapp\test_app\container
  Create an .env file in the directory, write the container registry user name and password, and save it.

  Code Block
  CONTAINER_REGISTRY_USERNAME_[container registry name]=[user name] CONTAINER_REGISTRY_PASSWORD_[container registry name]=[password]

  An example is shown below.

  Image Removed

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• Image Added

Coding the app

Now code as you like on Visual Studio Code. If you copy skeleton_sample_app etc., the source file name will be the one before copying (skeletonSampleApp.cpp for skeleton_sample_app), so please rename it if necessary. Below is an example.

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${SDK_DIR}\src\adamapp\test_app\Makefile
Before
PROG_NAME= SkeletonSampleApp
After
PROG_NAME= TestApp

${SDK_DIR}\src\adamapp\test_app\configuration.txt
Before
APPLICATION	SkeletonSampleApp
After
APPLICATION	TestApp

${SDK_DIR}\src\adamapp\test_app\container\deployment.template.json
Before
"APPLICATION_NAME=SkeletonSampleApp"
After
"APPLICATION_NAME=TestApp"

Build the app

When building, use the built-in functionality of the Azure IoT extension. In Visual Studio Code's Explorer Right-click on "${SDK_DIR}\src\adamapp\test_app\container\deployment.template.json" to display the build menu.

Select “Build IoT Edge Solution”. This operation only performs a build.

For your The Dockerfile provided with the SDK acquires the image from the i-PRO container registry and builds the image, so for the first build, you will be asked to log in to your the container registry. The following Below is an example when the container registry is "iprocv5xcontainerregistry.azurecr.io".of an error message.

ERROR: failed to solve: iprocv5xcontainerregistryiprocamsdk.azurecr.io/sdk/cadamappbase:1.0.0.2: failed to authorize: failed to fetch anonymous token: unexpected status: 401 Unauthorized

At this time, enter the following command on the Visual Studio Code terminal.

docker login iprocv5xcontainerregistryiprocamsdk.azurecr.io

Then enter Enter the Username and Password that are then displayed. Enter the container registry user name and password.

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ID and password. If you wish to use i-PRO's container registry, please log in using the username and password provided to you.

Username: [user name]
Password: [password]

If you want to use your own container registry, enter the following:

Username: sdk-containeradam-ro
Password: H291gWcZ7Tg6Eph+TbTrsDKyYgHLtWq1vQHPuxIOZb+ACRADu2w4

If Login Succeeded is displayed, the login is successful.Next, right-click ".

Then right click on ${SDK_DIR}\src\adamapp\test_app\container\deployment.template.json " and Select “Build Build and Push IoT Edge Solution”Solution. This operation builds and pushes to the container registry.

The build is done by running Docker buildx build as described in the Dockerfile.arm64v8 azureIoT file located under “ ${SDK_DIR}\src\adamapp\test_app\”. The environment name (arm64v8) after Dockerfile. is the architecture selected in the above step. (You can see the current architecture at the bottom of Visual Studio Code)

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Check the built image

If the build is successful, you can check the existence of the image with docker images. Below is an example.

$ docker images
REPOSITORY                                                             TAG             IMAGE ID       CREATED          SIZE
iprocv5xcontainerregistry.azurecr.io/azureiot/test_app  0.0.5-arm64v8   f1772ccfed77   35 minutes ago   91.4MB

Deploy to camera

Select the device you want to deploy from under "AZURE IOT HUB" in the bottom left, right-click and select "Deploy to one IoT Edge" to deploy it to the camera. What to deploy Follows "${SDK_DIR}\src\adamapp\test_app\container\deployment.template.json".

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Deployment Succeeded is displayed, the deployment is successful.

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Check runtime status on Azure

Log in to the Azure portal(Cloud Computing Services | Microsoft Azure) and select the IoT Edge device you added on the IoT Hub - IoT Edge screen.

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Check the operation of the app

Access the URL below with a PC that can connect to the camera.

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You can check the app operation as below. Below is an example of running skeleton_sample_app.

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Controlling Container version Adamapp using Azure IoT Explorer

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It is possible to control and check the Container version of Adamapp using Azure IoT Explorer published by Microsoft. The following describes the installation and initial settings of Azure IoT Exporlor.

Install

Follow Install and use Azure IoT explorer - Azure IoT | Microsoft Learn and install Azure IoT Explorer on your PC.

Initial setting

When you start Azure IoT Explorer, the following initial screen will appear, so select "Connect via IoT Hub connection string".

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Select the device you want to check from the displayed device (camera) list.

Checking the setting values with ModuleTwin

The settings values listed in the app settings (AppPrefs.json) can be checked from the cloud using Azure IoT's ModuleTwin mechanism.

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Setting the operation schedule

Use ModuleTwin to set the time zone in which the application will run.

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• After entering the settings, press "Save" at the top of the screen to apply the settings to the camera.

• Up to 8 can be set.

• If it is within any of the configured times, Container AdamApp for Azure IoT Edge will work.

• If the inference end time is later than the inference start time, the inference end time represents the next day.

• If scheduleField is empty, it will always operate.

• If the information is incorrect, the application will not start.

• Stop/start decisions are made at 15 second intervals. Therefore, the start and stop times will be delayed by up to 15 seconds.

Sending telemetry data from the device via cloud communication

Sending telemetry data

• Telemetry data can be sent from the device via cloud communication by calling the ADAM_SendTelemetry() function, which is valid only for Container AdamApp for Azure IoT Edge.

• Please specify values in JSON format for the arguments of this API. Please see the API specification for details.

• Device-to-cloud communication has a limit on the number of times it can communicate depending on the Azure IoT Hub settings. Please check here for more details.

• To control communication, sending is set to OFF by default. In order to send to the cloud, you must first turn on the sending function.

• There are two ways to turn on the transmission function: Module direct method and Module twin desired property. Please see below.

How to turn on using module direct method

Select the target Container Adamapp for Azure IoT Edge in Azure IoT Explorer.

Select "Module direct method" from the left menu. You can send a direct method on the screen below.

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The results will be displayed in a pop-up. If the status is 200, it is successful.

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How to set with Module twin desired property

Display the Module twin of the target Container Adamapp for Azure IoT Edge in Azure IoT Explorer.
Set as follows in “properties”.”desired”.”aplField”.

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How to check the settings

Setting values can be checked with Module twin.
Check the value of “properties”.”reported”.”aplField”.”azureSettings”.”telemetry”.

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Checking received telemetry data

Select the target Container Adamapp for Azure IoT Edge in Azure IoT Explorer.

Select "Telemetry" from the left menu.

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The string set in ADAM_SendTelemetry will be set as the value of the payload key.

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How to check the log

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App log

You can check messages output by ADAM_DEBUG_PRINT() within the app and logs output by libraries linked from the app. You can also check if there is an error.

• Log in to Azure portal(Cloud Computing Services | Microsoft Azure).

• Select the target IoT Hub.

• Select the target camera from "Device Management" and "IoT Edge" on the left.

• From the list of modules below, click the "Runtime Status" link for the app name you want to view logs for.

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camera pflog

By checking the log in the camera, you can also analyze the behavior when Container Adamapp for Azure IoT Edge is not working properly. Logs can be obtained by clicking the execution button below.

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Among the multiple log files, we will introduce the log files that are most related to Container Adamapp for Azure IoT Edge.

• cadam (files with file names starting with pf_cadam, pf_cadamCgi) cadam is a process that manages Container Adamapp for Azure IoT Edge.

• Azure IoT Edge runtime (files whose names start with pf_aziot-certd, pf_aziot-edged, pf_aziot-identityd, pf_aziot-keyd)Azure IoT Edge runtime communicates with Azure IoT Hub.

• Docker (files with file names starting with pf_docker, pf_containerd, pf_opa) Logs related to Docker operations. opa is used for security checks, and if the created deployment manifest contains content that violates the camera's security policy, a log will be output to this file.

Enhance Security Level of your Container

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This article describes techniques for strengthening container security when developing container applications.

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Examples of Security Measures in Container Apps Development

Run Vulnerability Checker against your Image

コンテナのセキュリティを強化する方法の一つとして、コンテナイメージ内の脆弱性をツールを用いて抽出し、それら脆弱性を可能な限り取り除いたり修正したりする方法があります。

以下では、コンテナイメージの脆弱性を検知するOSSのツールのうちTrivyとDockleを使用してコンテナイメージの脆弱性を抽出し、セキュリティ強化を図る例を説明します。

コンテナアプリの開発フローと、その中に脆弱性の抽出および対処を組込んだ例を下図に示します。脆弱性の抽出および対処は、早い段階から開発フローの中に組込み、実施することが推奨されます。最低限、イメージが製品リリースされる前の、実際の本番環境にデプロイされる前に必ず実施されるべきです。

本作業は、セキュリティに関するトレードオフの問題でもあります。抽出および対処にかかる時間や費用、頻度を考慮しなければなりません。しかし、セキュリティ上のリスクを最小限に抑えるために、脆弱性の抽出および対処は定期的に実施することが推奨されます。

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本図の開発フローの例では、

• コンテナイメージのビルド “Build Container Image” の工程の直後に、

• ツールによる脆弱性の抽出と設計者による対応判定 “Check & Judge Vulnerability” を実施し、

• 次にその判定で対応必要としたものに対し実際に処置をする “Modify Vulnerability” を実施する、

という例を示しています。

脆弱性抽出ツールはTrivyとDockleの2つ両方を使用する例を示しています。これら両方を使用する理由は、各ツールの抽出できる脆弱性の範囲が相異なるためです。Trivyは主にパッケージの脆弱性を抽出し、Dockleは例えば不要なファイルの検出や設定の不備の検出など、主にシステム関連の脆弱性を抽出します。両方のツールを使用することで、より包括的なコンテナイメージのセキュリティチェックを実施できます。これら2つのツールの使用方法の概略については以降の節で記述します。

また、本図では脆弱性チェックの対象として、自身の開発プロダクトであるアプリコンテナイメージだけでなく、その開発途中でマルチビルド等の目的でベースとして使用するコンテナイメージ(例： Debian の公式イメージなど) についても対象としています。その理由は使用するパッケージに対しての脆弱性を漏れなく調べるためなのですが、詳細は改めてTrivyの説明の節において記述します。

Trivy: Comprehensive Vulnerability Scanner

Trivyは、コンテナイメージやファイルシステムに存在する脆弱性を検出するオープンソースのスキャナです。主にOSパッケージやプログラミング言語のライブラリに関連する脆弱性を対象にしています。TrivyはAqua Security社によって開発・メンテナンスされており、コンテナ開発者にとって信頼性の高いツールの一つです。

Trivy の使い方の基本例を以下に示します。

(1)  Install Trivy:

まず、Trivy をインストールします。Trivyのリリースページから最新版のバイナリをダウンロードできます。下記リンクからTrivyのリリースページにアクセスしてください。

https://github.com/aquasecurity/trivy/releases

リリースページには、Linux、macOS、Windowsなどの各プラットフォーム向けのバイナリが用意されています。自分の環境に合ったバイナリを選択し、ダウンロードしてください。また、Trivyの公式ドキュメントには、各プラットフォームでのインストール方法が詳細に記載されていますので、そちらも参考にしてください。

Trivy は定期的に更新されていますので、最新版をインストールして使用するようにしてください。

(2)  Run Trivy:

インストールが完了したら、コマンドラインからTrivyを実行して、対象となるコンテナイメージの脆弱性をスキャンします。以下のコマンドは、your-image というコンテナイメージをスキャンする例です。

buildhost$ trivy image your-image

絞り込みを行う際は必要に応じて、Trivy のオプションを使用してスキャン対象や表示内容をカスタマイズできます。例えば、特定の重要度 (後述) 以上の脆弱性のみを表示する場合は、以下のようなコマンドを使用できます。

buildhost$ trivy image --severity CRITICAL,HIGH your-image

(3)  Check the result and determine how to deal with:

スキャンが完了すると、Trivy は検出された脆弱性の一覧を表示します。脆弱性の詳細や重要度（CRITICAL、HIGH、MEDIUM、LOW、UNKNOWN）が示され、修正が必要な箇所を特定しやすくなります。この結果をもとに、影響度などを加味しながらどれをどう対処していくのかを決定していきます。

参考で、以下に公式の ubuntu のイメージに対し trivy を実行した例 (オプション指定無し) の抜粋を示します。(実行例は Trivy は 0.38.3 を使用しています。)

Example execution of trivy: target image = ubuntu

Run Vulnerability Checker against your Image

One way to strengthen container security is to use tools to extract vulnerabilities in container images and remove or fix them as much as possible.

Below, we will explain an example of using Trivy and Dockle, two OSS tools for detecting vulnerabilities in container images, to extract vulnerabilities in container images and strengthen security.

The diagram below shows the development flow of a container app and an example of incorporating vulnerability extraction and countermeasures into it. It is recommended that vulnerability extraction and countermeasures be incorporated into the development flow from an early stage. At a minimum, this should be done before the image is released into production and deployed to an actual production environment.

This work is also a matter of security trade-offs. The time, cost, and frequency of extraction and treatment must be considered. However, to minimize security risks, it is recommended that vulnerabilities be identified and addressed on a regular basis.

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In the example development flow shown in this diagram, an example is shown.

• Immediately after the “Build Container Image” step,

• By extracting vulnerabilities using tools and conducting “Check & Judge Vulnerability” by designers,

• Next, carry out “Modify Vulnerability” to actually take action on what needs to be addressed based on the judgment.

This example uses both Trivy and Dockle as vulnerability extraction tools. The reason for using both of these is that each tool extracts a different range of vulnerabilities. Trivy mainly extracts vulnerabilities in packages. Dockle mainly extracts system-related vulnerabilities, such as detecting unnecessary files or misconfigurations. By using both tools, you can perform more comprehensive security checks on your container images. The following sections outline how to use these two tools.

In addition, in this figure, vulnerability checks are not limited to application container images that are self-developed products, but also container images that are used as a base for multi-build purposes during development (e.g., Debian official images, etc.) It also covers. The reason for this is to thoroughly check for vulnerabilities in the packages you use. The details will be described in the Trivy explanation section.

Trivy: Comprehensive Vulnerability Scanner

Trivy is an open source scanner that detects vulnerabilities in container images and file systems. It mainly targets vulnerabilities related to OS packages and programming language libraries. Trivy is developed and maintained by Aqua Security and is one of the most reliable tools for container developers.

Below is a basic example of how to use Trivy.

(1)  Install Trivy:

First, install Trivy. You can download the latest version of the binaries from the Trivy release page. Please access the Trivy release page from the link below.

https://github.com/aquasecurity/trivy/releases

The release page provides binaries for each platform, including Linux, macOS, and Windows. Select the binary that suits your environment and download it. Also, please refer to Trivy's official documentation, which has detailed instructions on how to install it on each platform.

Trivy is updated regularly, so be sure to install and use the latest version.

(2)  Run Trivy:

Once installed, run Trivy from the command line to scan the target container image for vulnerabilities. The following command is an example of scanning a container image called your-image.

buildhost$ trivy image your-image

When filtering, you can use Trivy's options to customize what is scanned and what is displayed, if necessary. For example, if you want to display only vulnerabilities of a certain severity level (described below), you can use a command like the following:

buildhost$ trivy image --severity CRITICAL,HIGH your-image

(3)  Check the result and determine how to deal with:

Once the scan is complete, Trivy displays a list of detected vulnerabilities. Vulnerability details and severity (CRITICAL, HIGH, MEDIUM, LOW, UNKNOWN) are shown, making it easier to identify areas that need fixing. Based on these results, we will decide which ones to deal with and how to deal with them, taking into consideration factors such as the degree of impact. For reference, below is an excerpt of an example of running trivy on an official ubuntu image (without specifying options). (The execution example uses Trivy 0.38.3.)

Example execution of trivy: target image = ubuntu

(4)  Note for use:

ここで、Trivyにかけるイメージについて一つ注意点があります。Trivy はパッケージの脆弱性をスキャンする際にパッケージ情報を参照しています。しかし、コンテナイメージのビルドプロセスによっては、パッケージ情報が最終プロダクトであるコンテナイメージに含まれないことがあります。この場合、Trivy がパッケージ脆弱性の検出に関連する情報を取得できず、その機能を利用できない可能性があります。

コンテナ開発者としては、Trivy を適切に活用するために、コンテナイメージにパッケージ情報を含めるか、あるいは Trivy のスキャン対象となるよう別の方法でパッケージ情報を提供することが重要です。例えば、Dockerfile の RUN コマンドでパッケージのインストールとクリーンアップを同時に行っている場合、パッケージ情報がコンテナイメージに含まれないことがあります。このような状況では、Trivy の利用に制限が生じるため、必要に応じてビルドプロセスを調整することが望ましいです。

一手段として、ベースとして使用したコンテナイメージにはパッケージ情報を残したままにしておき、そのイメージに対して Trivy を実行する方法があります。最終プロダクトのコンテナに取り込む対象物は開発者が把握しているはずですので、その対象物に対応するパッケージの脆弱性情報のみを Trivy の実行結果から抽出すればよいわけです。

以上、Trivy のようなツールを利用してコンテナイメージに含まれる脆弱性を定期的にチェックし、セキュリティリスクを低減させることが重要です。また、CI/CDパイプラインにTrivyを組み込むことで、自動化された脆弱性検出を実現し、開発プロセス全体のセキュリティを向上させることができます。

Dockle: Container Image Security Linter

Dockle は、コンテナイメージのセキュリティベストプラクティスに基づいて、潜在的な問題を特定するオープンソースのツールです。Dockleは、Dockerfile やイメージ設定など、主にシステム関連の脆弱性を検出します。GoodwithTech 社によって開発・メンテナンスされており、Trivy と同様にコンテナ開発者にとって有益なツールの一つです。

Dockle の使い方の基本例を以下に示します。

(1)  Install Dockle:

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(4)  Note for use:

Here, there is one thing to note about the image you give to Trivy. Trivy references package information when scanning packages for vulnerabilities. However, depending on the container image build process, package information may not be included in the final product, the container image. In this case, Trivy may not be able to retrieve information related to package vulnerability detection and may not be able to take advantage of that functionality.

As a container developer, it is important to include package information in your container images or otherwise provide package information for Trivy to scan in order to properly utilize Trivy. For example, if your Dockerfile's RUN command installs and cleans up packages at the same time, the package information may not be included in the container image. In these situations, there are limitations to the use of Trivy, so it is best to adjust the build process as necessary.

One option is to leave the package information in the container image you used as a base and run Trivy against that image. The developer knows what to include in the container of the final product. He only needs to extract vulnerability information for the package corresponding to the target from the Trivy execution results.

As mentioned above, it is important to regularly check for vulnerabilities in container images using tools like Trivy to reduce security risks. Additionally, by incorporating Trivy into your CI/CD pipeline, you can achieve automated vulnerability detection and improve security throughout your development process.

Dockle: Container Image Security Linter

Dockle is an open source tool that identifies potential issues based on container image security best practices. Dockle primarily detects system-related vulnerabilities, such as Dockerfiles and image configurations. It is developed and maintained by GoodwithTech and, like Trivy, is one of the most useful tools for container developers.

Below is a basic example of how to use Dockle.

(1)  Install Dockle:

First, install Dockle. You can download the latest version of the binaries from the Dockle release page. Please access Dockle's release page from the link below.

https://github.com/goodwithtech/dockle/releases リリースページには、Linux、macOS、Windowsなどの各プラットフォーム向けのバイナリが用意されています。自分の環境に合ったバイナリを選択し、ダウンロードしてください。また、Dockle の公式ドキュメントには、各プラットフォームでのインストール方法が詳細に記載されていますので、そちらも参考にしてください。

The release page provides binaries for each platform, including Linux, macOS, and Windows. Select the binary that suits your environment and download it. Also, please refer to Dockle's official documentation, which provides detailed instructions on how to install it on each platform.

(2)  Run Dockle:

インストールが完了したら、コマンドラインから Dockle を実行して、対象となるコンテナイメージのセキュリティベストプラクティスをチェックします。以下のコマンドは、your-image というコンテナイメージをチェックする例です。Once installed, run Dockle from the command line to check the security best practices for your container image. The following command is an example of checking a container image called your-image.

buildhost$ dockle your-image

絞り込みを行う際は必要に応じて、Dockle のオプションを使用してチェック対象や表示内容をカスタマイズできます。例えば、特定のチェック ID (後述) を無視する場合は、以下のように実行します。When filtering, you can use Dockle's options to customize what to check and what to display if necessary. For example, if you want to ignore a particular check ID (described below), run:

buildhost$ dockle --ignore CIS-DI-0001 your-image

(3)  Check the result and determine how to deal with:

チェックが完了すると、Dockle は検出された問題の一覧を表示します。各問題には、CIS（Center for Internet Security）ベンチマークに基づいたチェック ID が付与されており、対処すべき箇所を特定しやすくなります。この結果をもとに、影響度などを加味しながらどれをどう対処していくのかを決定していきます。

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-DI-0001 your-image

(3)  Check the result and determine how to deal with:

Once the check is complete, Dockle displays a list of detected issues. Each issue has a check ID based on Center for Internet Security (CIS) benchmarks to help you identify areas to address. Based on these results, you will decide which ones to deal with and how to deal with them, taking into consideration factors such as the degree of impact. For reference, below is an excerpt of an example of running Dockle on an Azure IoT Edge sample application image (no options specified).

Example execution of Dockle: target image = azureiotedge example application

As mentioned above, it is important to use tools like Dockle to regularly check for system-related issues in container images and reduce security risks, just like Trivy.

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• setgid file: grwxr-xr-x sbin/unix_chkpwd

INFO     - DKL-LI-0003: Only put necessary files

• unnecessary file : app/docker/linux/arm64v8/base/Dockerfile

• unnecessary file : app/docker/linux/arm32v7/base/Dockerfile

           <<<<........ SNIP ........>>>>

• unnecessary file : app/docker/windows/arm32v7/base/Dockerfile

以上、Trivy と同様に Dockle のようなツールを利用してコンテナイメージに含まれるシステム関連の問題を定期的にチェックし、セキュリティリスクを低減させることが重要です。また、CI/CD パイプラインに Dockle を組み込むことで、自動化されたセキュリティベストプラクティスのチェックを実現し、開発プロセス全体のセキュリティを向上させることができます。

Force-Limit on Access to Host Resources

セキュリティ上の理由から、i-PROカメラ上で動作するコンテナはアクセス可能なi-PROカメラのホスト側の権限やリソースが強制的に制限されています。Docker API に対し、i-PROに許可されていない権限やリソースの場所、範囲外の値のオプションを指定したコンテナを起動しようとした場合、ホスト側のチェック機構がそれら要求を拒否する仕組みが搭載されています (下記の図を参照)。

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上記の制約下において、i-PROが許可しているオプション一式が事前設定されているテンプレートを SDK のビルド環境にて提供しています。このテンプレートにはコンテナアプリケーションが起動許可されるために必要かつ十分な設定となっており、上記のような権限やリソースに関する設定は変更せずにそのまま使用可能となっています (コンテナ名などの個別対応が必要なものを除く)。開発されるコンテナアプリケーションからアクセスが必要な権限やリソースに対して、上記テンプレートに事前設定されていない場合や、ご自身で追加、変更した設定がi-PROカメラのホスト側から拒否される場合には、設計、設定の見直しをお願いします。You can also incorporate Dockle into your CI/CD pipeline to provide automated security best practice checks and improve security throughout your development process.

Force-Limit on Access to Host Resources

For security reasons, the permissions and resources of the i-PRO camera host that can be accessed by containers running on the i-PRO camera are forcibly restricted. If an attempt is made to start a container that specifies permissions, resource locations, or out-of-range options for Docker API that are not allowed by i-PRO, a check mechanism on the host side will reject the request. (see diagram below).

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Under the above constraints, we provide a template in the SDK build environment that is preconfigured with a set of options allowed by i-PRO. This template has the necessary and sufficient settings for the container application to be allowed to start, and can be used as is without changing settings related to permissions and resources such as the above (individual settings such as container name etc. (excluding those that require action).
If the permissions and resources that need to be accessed from the container application being developed are not pre-configured in the above template, or if the settings you have added and/or changed yourself are rejected by the i-PRO camera host. Please review the design and/or settings.

Checkpoints if things don't work in the WSL environment

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If it does not work in WSL environment, please check the following.

• The following must be enabled in the Visual Studio Code "LOCAL" extension

  • Dev Containers

  • Remote - SSH, Remote - SSH: Editing Configuration FIles, Remote - Tunnels, Remote Development, Remote Explorer

  • WSL

• The following must be enabled in Visual Studio Code's "WSL: UBUNTU-20.04" extension:

  • Azure Account

  • Azure IoT Edge

  • Azure IoT Hub

• "WSL: Ubuntu-20.04" is displayed at the bottom left of the Visual Studio Code screen.

  

• If permission denied is displayed in Build IoT Edge Solution, check whether the current user has access rights to the target directory.

  Code Block
  sudo chown -r ipro:ipro [development directory] ※ipro:ipro is an example, so please set it according to each environment.

  Run the above to change the owner.

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