tern

tern

容器镜像软件物料清单生成工具

Tern是一款开源的容器镜像检查工具,用于生成软件物料清单(SBOM)。通过逐层分析容器镜像,Tern收集操作系统和软件包的元数据,生成详细报告。支持多种输出格式如人类可读、JSON和HTML,有助于深入了解容器内容、进行合规性检查和安全分析。Tern适用于容器开发者、DevOps工程师及关注容器内容的技术人员。

TernSBOM容器软件包检查DockerGithub开源项目

Tern

Pull Request Lint and Test CII Best Practices License

Welcome to the Tern Project

Tern is a software package inspection tool that can create a Software Bill of Materials (SBOM) for containers. It's written in Python3 with a smattering of shell scripts.

Table of Contents

What is Tern?<a name="what-is-tern">

Tern is an inspection tool to find the metadata of the packages installed in a container image. The overall operation looks like this:

  1. It analyzes the first layer of the container image to collect information like distro type, package format, and package managers.
  2. It then executes scripts from the "command library" in a chroot environment to collect information about packages installed in that layer.
  3. With that information as a starting point, it continues to analyze the subsequent layers in the container image.
  4. Once done, it generates a report of packages with their metadata. Several formats are available. The report, in its default format, provides a layer by layer, explanation of the various software components imported. If a Dockerfile is provided, the report indicates the Dockerfile lines corresponding to each of the file system layers.

Tern gives you a deeper understanding of your container's bill of materials so you can make better decisions about your container based infrastructure, integration and deployment strategies. It's also a good tool if you are curious about the contents of the container images you have built.

Tern quick demo

Getting Started<a name="getting-started"/>

GitHub Action<a name="github-action"/>

A GitHub Action is available if you just want to scan Docker container images to find the Base OS and packages installed. Please contribute changes here. Thanks to Jeroen Knoops @JeroenKnoops for their work on this.

Getting Started on Linux<a name="getting-started-on-linux">

If you have a Linux OS you will need a distro with a kernel version >= 4.0 (Ubuntu 16.04 or newer or Fedora 25 or newer are good selections) and will need to install the following requirements:

  • Git (Installation instructions can be found here: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
  • attr (sudo apt-get install attr or sudo dnf install attr)
  • Python 3.6 or newer (sudo apt-get install python3.6(3.7) or sudo dnf install python36(37))
  • Pip (sudo apt-get install python3-pip).
  • jq (sudo apt-get install jq or sudo dnf install jq)
  • skopeo (See here for installation instructions or building from source)

Some distro versions have all of these except attr, jq, and/or skopeo preinstalled. attr and jq are common utilities and are available via the package manager. skopeo has only recently been packaged for common Linux distros. If you don't see your distro in the list, your best bet is building from source, which is reasonably straightforward if you have Go installed.

For analyzing Dockerfiles and to use the "lock" function

NOTE: We do not provide advice on the usage of Docker Desktop

Once installed, make sure the docker daemon is running.

Create a python3 virtual environment:

python3 -m venv ternenv
cd ternenv

NOTE: Your OS might distribute each Python version separately. For example, on Ubuntu LTS, Python 2.7 is linked to python2 and Python 3.6 is linked to python3. I develop with Python 3.7 which is installed separately with no symlinks. In this case, I use the binary. The binaries are usually installed in /usr/bin/python.

Activate the virtual environment:

source bin/activate

NOTE: This specific activate script only works for Bash shells. If you need to activate a Fish Shell or C Shell you should use source bin/activate.fish or source bin/activate.csh, respectively.

Install tern:

pip install tern

Run Tern:

tern report -o output.txt -i debian:buster

Getting Started with Docker<a name="getting-started-with-docker">

Docker is the most widely used tool to build and run containers. If you already have Docker installed, you can run Tern by building a container with the Dockerfile provided.

Clone this repository:

git clone https://github.com/tern-tools/tern.git

Build the Docker image (called ternd here). You may need to use sudo:

docker build -f docker/Dockerfile -t ternd .

This will install the latest release of tern using pip.

If you want to build a Docker image containing the latest changes to tern, run:

python setup.py sdist
docker build -f ci/Dockerfile -t ternd .

NOTE: By default, Tern will run with logging turned on. If you would like to silent the terminal output when running the ternd container, make the following change to the Dockerfile ENTRYPOINT before building:

--- a/Dockerfile
+++ b/Dockerfile
-ENTRYPOINT ["tern"]
+ENTRYPOINT ["tern", "-q"]

Run the ternd container image

docker run --rm ternd report -i debian:buster

If you are using this container to analyze Dockerfiles and to use the "lock" feature, then you must volume mount the docker socket. We have a convenience script which will do that for you.

./docker_run.sh ternd "report -i debian:buster" > output.txt

To produce a json report run

./docker_run.sh ternd "report -f json -i debian:buster"

Tern is not distributed as Docker images yet. This is coming soon. Watch the Project Status for updates.

WARNING: If using the --driver fuse or --driver overlay2 storage driver options, then the docker image needs to run as privileged.

docker run --privileged -v /var/run/docker.sock:/var/run/docker.sock ternd --driver fuse report -i debian:buster

You can make this change to the docker_run.sh script to make it easier.

Creating a Kubernetes Job<a name="k8s-job">

A Tern container can be deployed on Kubernetes as a Job. However, a host mount is required to retrieve the reports. We will describe below how to create a Kubernetes Job within minikube.

To install minikube, follow these instructions. If using a virtual machine manager, make sure it supports volume mounts. We will be using VirtualBox in this example.

Download the existing Tern Dockerfile

wget https://raw.githubusercontent.com/tern-tools/tern/main/docker/Dockerfile

Start minikube

minikube start --driver=virtualbox

Use minikube to build the Tern container image

minikube image build -t tern:test -f Dockerfile .

Once build has completed, you should see the image by running minikube image ls. It should look something like docker.io/library/tern:test.

We are now ready to create a Job. You can modify the following YAML according to your host's filesystem:

apiVersion: batch/v1
kind: Job
metadata:
  name: tern
spec:
  template:
    spec:
      restartPolicy: Never
      containers:
      - image: docker.io/library/tern:test
	# in order run the job for other containers, replace the "-i" argument here
        command: ["tern", "report", "-i", "docker.io/library/debian:buster", "-o", "/host/report.txt"]
        name: tern-example
        volumeMounts:
          - name: host-mount
            mountPath: /host # this path exists in the pod
      volumes:
      - name: host-mount # create a corresponding directory on the host
        hostPath:
          path: /path/to/tern/reports # this path must exist on the host

We can now deploy Tern on Kubernetes

minikube kubectl -- apply -f tern-example.yaml

To check the status of the Job, you can run minikube kubectl -- describe job.batch/tern. You should be able to see report.txt in /path/to/tern/reports/.

Getting Started with Vagrant<a name="getting-started-with-vagrant">

Vagrant is a tool to setup an isolated virtual software development environment. If you are using Windows or Mac OSes and want to run Tern from the command line (not in a Docker container) this is the best way to get started as Tern does not run natively in a Mac OS or Windows environment at this time.

Install

Follow the instructions on the VirtualBox website to download VirtualBox on your OS.

Follow the instructions on the website to install Vagrant for your OS.

Create a Vagrant environment

NOTE: The following steps will install the latest PyPI release version of Tern. If you want to install Tern from the tip of master, please instead follow "Setting up a development environment on Mac and Windows" in the contributing guide.

In your terminal app, run the following commands.

Clone this repository:

git clone https://github.com/tern-tools/tern.git

Bring up the Vagrant box:

cd tern/vagrant
vagrant up

SSH into the created VM:

vagrant ssh

Run:

tern report -i debian:buster -o output.txt

Using Tern<a name="using-tern">

WARNING: The CLI has changed since the last release. Visit Tern's PyPI project page to find the correct CLI options or just run tern -h.

Tern creates a report containing the Software Bill of Materials (SBOM) of a container image, including notes about how it collects this information, and files for which it has no information about. Currently, Tern supports containers only built using Docker using image manifest version 2, schema 2. Docker image manifest version 2, schema 1 has been deprecated by Docker. Tern will support container images created using Docker version 19.03.0 or later. Docker is the most ubiquitous type of container image that exists so the project started with a focus on those. However, it is architected to support other images that closely follow the OCI image spec.

Generating an SBOM report for a Docker image<a name="sbom-for-docker-image">

If you have a Docker image pulled locally and want to inspect it

tern report -i debian:jessie

The SBOM of packages that are installed in the Docker image and how Tern got this information will be printed to the console. To direct this output to a file, use the -o file_name command line option. If you encounter any errors, please file an issue.

Generating an SBOM report from a Dockerfile<a name="sbom-for-dockerfile">

You can provide a Dockerfile to Tern to figure out the Software Bill of Materials and other information. Tern will build the image, analyze it with respect to the Dockerfile and discard the image. This is useful to engineers who are developing a Dockerfile for their app or in a container build and release pipeline.

tern report -d samples/photon_git/Dockerfile

The SBOM of packages you would be shipping if you were to use the given Dockerfile will print to the console. To direct the output to a file, use the -o file_name command line option. Feel free to try this out on the other sample Dockerfiles in the samples directory or on Dockerfiles you may be working with. If it doesn't work for you, please file an issue.

Generating a locked Dockerfile<a name="dockerfile-lock">

Because of the way Docker builds containers, Dockerfiles are generally not declarative or reflective of what ultimately gets included in the container image that gets produced. Pinning information in your Dockerfile (base OS, packages, etc.) can help create more reproducible container images should your Dockerfile be distributed to other parties. If you have a Dockerfile that you would like to lock to a more reproducible version, Tern can help.

tern lock Dockerfile

The locked Dockerfile will be created in Dockerfile.lock unless an output file is otherwise specified. To specify an output file

tern lock Dockerfile -o output.txt

If the packages are not pinned in the resulting Dockerfile.lock or output file that gets produced, it is because 1) Tern does not know the version of the packages to pin (i.e. unable to get this information from the package manager) or 2) your Dockerfile failed to build. In the case of a failed Dockerfile build, Tern only builds the base image and tries to pin what it can. If you encounter any errors, please file an issue.

Report Formats<a name="report-formats">

Tern creates SBOM reports suitable to read over or to provide to another tool for consumption. A collection of sample reports is available to view here.

Understanding the Reports<a name="understanding-the-reports">

Tern provides a handful of different reporting styles that may work better for different applications of distribution, interoperability and comprehension. Understanding these reports will vary slightly between formats, but the information in the different report formats will generally be the same with varying degrees of package metadata detail. In all report formats, information about the version of Tern that generated the report and any applicable extension information will be at the top of the report followed by information about the metadata found in the container, organized sequentially by layer.

The base layer (Layer 1) will provide operating system information on which the container is based, the Dockerfile command that created the layer, the package retrieval method and any packages found in the layer. Note that the operating system information may be different than the container that Tern is generating an SBOM for. For example, the golang container's base OS is actually Debian GNU/Linux 10 (buster). For each subsequent layer in the container, information about the Dockerfile command that created the container layer, any warnings about unrecognized Dockerfile commands, the package retrieval method and package information is provided. If Tern doesn't find any package information in a layer, it will report packages found in the layer as "None". File licenses may also be available in the reports if Tern is run using scancode.

More information about specific reporting formats can be found below and in the tern/classes directory where the properties being reported on are explained in the .py files -- specifically, image_layer.py, package.py, and file_data.py.

Human Readable Format<a name="report-human-readable">

The default report Tern produces is a human readable, high-level overview. The object of this report is to give the container developer a deeper understanding of what is installed in a container

编辑推荐精选

Vora

Vora

免费创建高清无水印Sora视频

Vora是一个免费创建高清无水印Sora视频的AI工具

Refly.AI

Refly.AI

最适合小白的AI自动化工作流平台

无需编码,轻松生成可复用、可变现的AI自动化工作流

酷表ChatExcel

酷表ChatExcel

大模型驱动的Excel数据处理工具

基于大模型交互的表格处理系统,允许用户通过对话方式完成数据整理和可视化分析。系统采用机器学习算法解析用户指令,自动执行排序、公式计算和数据透视等操作,支持多种文件格式导入导出。数据处理响应速度保持在0.8秒以内,支持超过100万行数据的即时分析。

AI工具酷表ChatExcelAI智能客服AI营销产品使用教程
TRAE编程

TRAE编程

AI辅助编程,代码自动修复

Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。

AI工具TraeAI IDE协作生产力转型热门
AIWritePaper论文写作

AIWritePaper论文写作

AI论文写作指导平台

AIWritePaper论文写作是一站式AI论文写作辅助工具,简化了选题、文献检索至论文撰写的整个过程。通过简单设定,平台可快速生成高质量论文大纲和全文,配合图表、参考文献等一应俱全,同时提供开题报告和答辩PPT等增值服务,保障数据安全,有效提升写作效率和论文质量。

AI辅助写作AI工具AI论文工具论文写作智能生成大纲数据安全AI助手热门
博思AIPPT

博思AIPPT

AI一键生成PPT,就用博思AIPPT!

博思AIPPT,新一代的AI生成PPT平台,支持智能生成PPT、AI美化PPT、文本&链接生成PPT、导入Word/PDF/Markdown文档生成PPT等,内置海量精美PPT模板,涵盖商务、教育、科技等不同风格,同时针对每个页面提供多种版式,一键自适应切换,完美适配各种办公场景。

AI办公办公工具AI工具博思AIPPTAI生成PPT智能排版海量精品模板AI创作热门
潮际好麦

潮际好麦

AI赋能电商视觉革命,一站式智能商拍平台

潮际好麦深耕服装行业,是国内AI试衣效果最好的软件。使用先进AIGC能力为电商卖家批量提供优质的、低成本的商拍图。合作品牌有Shein、Lazada、安踏、百丽等65个国内外头部品牌,以及国内10万+淘宝、天猫、京东等主流平台的品牌商家,为卖家节省将近85%的出图成本,提升约3倍出图效率,让品牌能够快速上架。

iTerms

iTerms

企业专属的AI法律顾问

iTerms是法大大集团旗下法律子品牌,基于最先进的大语言模型(LLM)、专业的法律知识库和强大的智能体架构,帮助企业扫清合规障碍,筑牢风控防线,成为您企业专属的AI法律顾问。

SimilarWeb流量提升

SimilarWeb流量提升

稳定高效的流量提升解决方案,助力品牌曝光

稳定高效的流量提升解决方案,助力品牌曝光

Sora2视频免费生成

Sora2视频免费生成

最新版Sora2模型免费使用,一键生成无水印视频

最新版Sora2模型免费使用,一键生成无水印视频

下拉加载更多