6.3 KiB
type | stage | group | info |
---|---|---|---|
reference, howto | Secure | Composition Analysis | To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#designated-technical-writers |
Dependency Scanning Analyzers (ULTIMATE)
Dependency Scanning relies on underlying third-party tools that are wrapped into what we call "Analyzers". An analyzer is a dedicated project that wraps a particular tool to:
- Expose its detection logic.
- Handle its execution.
- Convert its output to the common format.
This is achieved by implementing the common API.
Dependency Scanning supports the following official analyzers:
The analyzers are published as Docker images, which Dependency Scanning uses to launch dedicated containers for each analysis.
Dependency Scanning is pre-configured with a set of default images that are maintained by GitLab, but users can also integrate their own custom images.
Official default analyzers
Any custom change to the official analyzers can be achieved by using an
environment variable in your .gitlab-ci.yml
.
Using a custom Docker mirror
You can switch to a custom Docker registry that provides the official analyzer
images under a different prefix. For instance, the following instructs Dependency
Scanning to pull my-docker-registry/gl-images/gemnasium
instead of registry.gitlab.com/gitlab-org/security-products/analyzers/gemnasium
.
In .gitlab-ci.yml
define:
include:
template: Dependency-Scanning.gitlab-ci.yml
variables:
SECURE_ANALYZERS_PREFIX: my-docker-registry/gl-images
This configuration requires that your custom registry provides images for all the official analyzers.
Selecting specific analyzers
You can select the official analyzers you want to run. Here's how to enable
bundler-audit
and gemnasium
while disabling all the other default ones.
In .gitlab-ci.yml
define:
include:
template: Dependency-Scanning.gitlab-ci.yml
variables:
DS_DEFAULT_ANALYZERS: "bundler-audit,gemnasium"
bundler-audit
runs first. When merging the reports, Dependency Scanning
removes the duplicates and keeps the bundler-audit
entries.
Disabling default analyzers
Setting DS_DEFAULT_ANALYZERS
to an empty string disables all the official
default analyzers. In .gitlab-ci.yml
define:
include:
template: Dependency-Scanning.gitlab-ci.yml
variables:
DS_DEFAULT_ANALYZERS: ""
That's needed when one totally relies on custom analyzers.
Custom analyzers
You can provide your own analyzers by
defining CI jobs in your CI configuration. For consistency, you should suffix your custom Dependency
Scanning jobs with -dependency_scanning
. Here's how to add a scanning job that's based on the
Docker image my-docker-registry/analyzers/nuget
and generates a Dependency Scanning report
gl-dependency-scanning-report.json
when /analyzer run
is executed. Define the following in
.gitlab-ci.yml
:
nuget-dependency_scanning:
image:
name: "my-docker-registry/analyzers/nuget"
script:
- /analyzer run
artifacts:
reports:
dependency_scanning: gl-dependency-scanning-report.json
The Security Scanner Integration documentation explains how to integrate custom security scanners into GitLab.
Analyzers data
The following table lists the data available for each official analyzer.
Property \ Tool | Gemnasium | bundler-audit | Retire.js |
---|---|---|---|
Severity | 𐄂 | ✓ | ✓ |
Title | ✓ | ✓ | ✓ |
File | ✓ | ⚠ | ✓ |
Start line | 𐄂 | 𐄂 | 𐄂 |
End line | 𐄂 | 𐄂 | 𐄂 |
External ID (e.g., CVE) | ✓ | ✓ | ⚠ |
URLs | ✓ | ✓ | ✓ |
Internal doc/explanation | ✓ | 𐄂 | 𐄂 |
Solution | ✓ | ✓ | 𐄂 |
Confidence | 𐄂 | 𐄂 | 𐄂 |
Affected item (e.g. class or package) | ✓ | ✓ | ✓ |
Source code extract | 𐄂 | 𐄂 | 𐄂 |
Internal ID | ✓ | 𐄂 | 𐄂 |
Date | ✓ | 𐄂 | 𐄂 |
Credits | ✓ | 𐄂 | 𐄂 |
- ✓ => we have that data
- ⚠ => we have that data, but it's partially reliable, or we need to extract that data from unstructured content
- 𐄂 => we don't have that data, or it would need to develop specific or inefficient/unreliable logic to obtain it.
The values provided by these tools are heterogeneous, so they are sometimes
normalized into common values (e.g., severity
, confidence
, etc).