Integrate Docker Scout with Artifactory
Integrating Docker Scout with JFrog Artifactory lets you run image analysis automatically on images in Artifactory registries.
Local image analysis
You can analyze Artifactory images for vulnerabilities locally using Docker Desktop or the Docker CLI. You first need to authenticate with JFrog Artifactory using the
docker login
command. For example:
docker login {URL}
情報
For cloud-hosted Artifactory you can find the credentials for your Artifactory repository by selecting it in the Artifactory UI and then the Set Me Up button.
Remote image analysis
To automatically analyze images running in remote environments you need to deploy the Docker Scout Artifactory agent. The agent is a standalone service that analyzes images and uploads the result to Docker Scout. You can view the results using the Docker Scout Dashboard.
How the agent works
The Docker Scout Artifactory agent is available as an image on Docker Hub. The agent works by continuously polling Artifactory for new images. When it finds a new image, it performs the following steps:
- Pull the image from Artifactory
- Analyze the image
- Upload the analysis result to Docker Scout
The agent records the Software Bill of Materials (SBOM) for the image, and the SBOMs for all of its base images. The recorded SBOMs include both Operating System (OS)-level and application-level programs or dependencies that the image contains.
Additionally, the agent sends the following metadata about the image to Docker Scout:
- The source repository URL and commit SHA for the image
- Build instructions
- Build date
- Tags and digest
- Target platforms
- Layer sizes
The agent never transacts the image itself, nor any data inside the image, such as code, binaries, and layer blobs.
The agent doesn't detect and analyze pre-existing images. It only analyzes images that appear in the registry while the agent is running.
Deploy the agent
This section describes the steps for deploying the Artifactory agent.
Prerequisites
Before you deploy the agent, ensure that you meet the prerequisites:
- The server where you host the agent can access the following resources over
the network:
- Your JFrog Artifactory instance
hub.docker.com
, port 443, for authenticating with Dockerapi.dso.docker.com
, port 443, for transacting data to Docker Scout
- The registries are Docker V2 registries. V1 registries aren't supported.
The agent supports all versions of JFrog Artifactory and JFrog Container Registry.
Create the configuration file
You configure the agent using a JSON file. The agent expects the configuration
file to be in /opt/artifactory-agent/data/config.json
on startup.
The configuration file includes the following properties:
Property | Description |
---|---|
agent_id | Unique identifier for the agent. |
docker.organization_name | Name of the Docker organization. |
docker.username | Username of the admin user in the Docker organization. |
docker.pat | Personal access token of the admin user with read and write permissions. |
artifactory.base_url | Base URL of the Artifactory instance. |
artifactory.username | Username of the Artifactory user with read permissions that the agent will use. |
artifactory.password | Password or API token for the Artifactory user. |
artifactory.image_filters | Optional: List of repositories and images to analyze. |
If you don't specify any repositories in artifactory.image_filters
, the agent
runs image analysis on all images in your Artifactory instance.
The following snippet shows a sample configuration:
{
"agent_id": "acme-prod-agent",
"docker": {
"organization_name": "acme",
"username": "mobythewhale",
"pat": "dckr_pat__dsaCAs_xL3kNyupAa7dwO1alwg"
},
"artifactory": [
{
"base_url": "https://acme.jfrog.io",
"username": "acmeagent",
"password": "hayKMvFKkFp42RAwKz2K",
"image_filters": [
{
"repository": "dev-local",
"images": ["internal/repo1", "internal/repo2"]
},
{
"repository": "prod-local",
"images": ["staging/repo1", "prod/repo1"]
}
]
}
]
}
Create a configuration file and save it somewhere on the server where you plan
to run the agent. For example, /var/opt/artifactory-agent/config.json
.
Run the agent
The following example shows how to run the Docker Scout Artifactory agent using
docker run
. This command creates a bind mount for the directory containing the
JSON configuration file created earlier at /opt/artifactory-agent/data
inside
the container. Make sure the mount path you use is the directory containing the
config.json
file.
重要
Use the
v1
tag of the Artifactory agent image. Don't use thelatest
tag as doing so may incur breaking changes.
$ docker run \
--mount type=bind,src=/var/opt/artifactory-agent,target=/opt/artifactory-agent/data \
docker/artifactory-agent:v1
Analyzing pre-existing data
By default the agent detects and analyzes images as they're created and
updated. If you want to use the agent to analyze pre-existing images, you
can use backfill mode. Use the --backfill-from=TIME
command line option,
where TIME
is an ISO 8601 formatted time, to run the agent in backfill mode.
If you use this option, the agent analyzes all images pushed between that
time and the current time when the agent starts, then exits.
For example:
$ docker run \
--mount type=bind,src=/var/opt/artifactory-agent,target=/opt/artifactory-agent/data \
docker/artifactory-agent:v1 --backfill-from=2022-04-10T10:00:00Z
When running a backfill multiple times, the agent won't analyze images that
it's already analyzed. To force re-analysis, provide the --force
command
line flag.
View analysis results
You can view the image analysis results in the Docker Scout Dashboard.
Go to Images page in the Docker Scout Dashboard.
This page displays the Docker Scout-enabled repositories in your organization.
Select the image in the list.
Select the tag.
When you have selected a tag, you're taken to the vulnerability report for that tag. Here, you can select if you want to view all vulnerabilities in the image, or vulnerabilities introduced in a specific layer. You can also filter vulnerabilities by severity, and whether or not there's a fix version available.