dd-import

A utility to (re-)import findings and language data into DefectDojo

Findings and languages can be imported into DefectDojo via an API. To make automated build and deploy pipelines easier to implement, dd-import provides some convenience functions:

Product types, products, engagements and tests will be created if they are not existing. This avoids manual preparation in DefectDojo or complicated steps within the pipeline.
Product types, products, engagements and tests are referenced by name. This make pipelines more readable than using IDs.
Build information for build_id, commit_hash and branch_tag can be updated when uploading findings.
No need to deal with curl and its syntax within the pipeline. This makes pipelines shorter and better readable.
All parameters are provided via environment variables, which works well with pipeline definitions like GitHub Actions or GitLab CI.

User guide

Installation and commands

Python

dd-import can be installed with pip. Only Python 3.8 and up is supported.

pip install dd-import

The command dd-reimport-findings re-imports findings into DefectDojo. Even though the name suggests otherwise, you do not need to do an initial import first.

The command dd-import-languages imports languages data that have been gathered with the tool cloc, see Languages and lines of code for more details.

Docker

Docker images can be found in https://hub.docker.com/r/maibornwolff/dd-import.

A re-import of findings can be started with

docker run --rm dd-import:latest dd-reimport-findings.sh

Importing languages data can be started with

docker run --rm dd-import:latest dd-import-languages.sh

Please note you have to set the environment variables as described below and mount a folder containing the file with scan results when running the docker container.

/usr/local/dd-import is the working directory of the docker image, all commands are located in the /usr/local/dd-import/bin folder.

Parameters

All parameters need to be provided as environment variables:

Parameter	Re-import findings	Import languages	Remark
DD_URL	Mandatory	Mandatory	Base URL of the DefectDojo instance
DD_API_KEY	Mandatory	Mandatory	Shall be defined as a secret, eg. a protected variable in GitLab or an encrypted secret in GitHub
DD_PRODUCT_TYPE_NAME	Mandatory	Mandatory	If a product type with this name does not exist, it will be created
DD_PRODUCT_NAME	Mandatory	Mandatory	If a product with this name does not exist, it will be created
DD_ENGAGEMENT_NAME	Mandatory	-	If an engagement with this name does not exist for the given product, it will be created
DD_ENGAGEMENT_TARGET_START	Optional	-	Format: YYYY-MM-DD, default: `today`. The target start date for a newly created engagement.
DD_ENGAGEMENT_TARGET_END	Optional	-	Format: YYYY-MM-DD, default: `2999-12-31`. The target start date for a newly created engagement.
DD_TEST_NAME	Mandatory	-	If a test with this name does not exist for the given engagement, it will be created
DD_TEST_TYPE_NAME	Mandatory	-	From DefectDojo's list of test types, eg. `Trivy Scan`
DD_FILE_NAME	Optional	Mandatory
DD_ACTIVE	Optional	-	Default: `true`
DD_VERIFIED	Optional	-	Default: `true`
DD_MINIMUM_SEVERITY	Optional	-
DD_GROUP_BY	Optional	-	Group by file path, component name, component name + version
DD_PUSH_TO_JIRA	Optional	-	Default: `false`
DD_CLOSE_OLD_FINDINGS	Optional	-	Default: `true`
DD_CLOSE_OLD_FINDINGS_PRODUCT_SCOPE	Optional	-	Default: `false`
DD_DO_NOT_REACTIVATE	Optional	-	Default: `false`
DD_VERSION	Optional	-
DD_ENDPOINT_ID	Optional	-
DD_SERVICE	Optional	-
DD_BUILD_ID	Optional	-
DD_COMMIT_HASH	Optional	-
DD_BRANCH_TAG	Optional	-
DD_API_SCAN_CONFIGURATION_ID	Optional	-	Id of the API scan configuration for API based parsers, e.g. SonarQube
DD_SOURCE_CODE_MANAGEMENT_URI	Optional	-
DD_SSL_VERIFY	Optional	Optional	Disable SSL verification by setting to `false` or `0`. Default: `true`
DD_EXTRA_HEADER_1	Optional	Optional	If extra header key is needed for auth in wafs or similar
DD_EXTRA_HEADER_1_VALUE	Optional	Optional	The corresponding value for extra header key
DD_EXTRA_HEADER_2	Optional	Optional	If extra header key is needed for auth in wafs or similar
DD_EXTRA_HEADER_2_VALUE	Optional	Optional	The corresponding value for extra header key

Usage

This snippet from a GitLab CI pipeline serves as an example how dd-import can be integrated to upload data during build and deploy using the docker image:

variables:
  DD_PRODUCT_TYPE_NAME: "Showcase"
  DD_PRODUCT_NAME: "DefectDojo Importer"
  DD_ENGAGEMENT_NAME: "GitLab"

...

trivy:
  stage: test
  tags:
    - build
  variables:
    GIT_STRATEGY: none
  before_script:
    - export TRIVY_VERSION=$(wget -qO - "https://api.github.com/repos/aquasecurity/trivy/releases/latest" | grep '"tag_name":' | sed -E 's/.*"v([^"]+)".*/\1/')
    - echo $TRIVY_VERSION
    - wget --no-verbose https://github.com/aquasecurity/trivy/releases/download/v${TRIVY_VERSION}/trivy_${TRIVY_VERSION}_Linux-64bit.tar.gz -O - | tar -zxvf -
  allow_failure: true
  script:
    - ./trivy --exit-code 0 --no-progress -f json -o trivy.json maibornwolff/dd-import:latest
  artifacts:
    paths:
    - trivy.json
    when: always
    expire_in: 1 day

cloc:
  stage: test
  image: node:16
  tags:
    - build
  before_script:
    - npm install -g cloc
  script:
    - cloc src --json -out cloc.json
  artifacts:
    paths:
    - cloc.json
    when: always
    expire_in: 1 day

upload_trivy:
  stage: upload
  image: maibornwolff/dd-import:latest
  needs:
    - job: trivy
      artifacts: true  
  variables:
    GIT_STRATEGY: none
    DD_TEST_NAME: "Trivy"
    DD_TEST_TYPE_NAME: "Trivy Scan"
    DD_FILE_NAME: "trivy.json"
  script:
    - dd-reimport-findings.sh

upload-cloc:
  image: maibornwolff/dd-import:latest
  needs:
    - job: cloc
      artifacts: true  
  stage: upload
  tags:
    - build
  variables:
    DD_FILE_NAME: "cloc.json"
  script:
    - dd-import-languages.sh

variables - Definition of some environment variables that will be used for several uploads. DD_URL and DD_API_KEY are not defined here because they are protected variables for the GitLab project.
trivy - Example for a vulnerability scan with trivy. Output will be stored in JSON format (trivy.json).
cloc - Example how to calculate the lines of code with cloc. Output will be stored in JSON format (cloc.json).
upload_trivy - This step will be executed after the trivy step, gets its output file and sets some variables specific for this step. Then the script to import the findings from this scan is executed.
upload_cloc - This step will be executed after the cloc step, gets its output file and sets some variables specific for this step. Then the script to import the language data is executed.

Another example, showing how to use dd-import within a GitHub Action, can be found in dd-import_example.yml.

Developer guide

Testing

./bin/runUnitTests.sh - Runs the unit tests and reports the test coverage.

./bin/runDockerUnitTests.sh - First creates the docker image and then starts a docker container in which the unit tests are executed.

License

Licensed under the 3-Clause BSD License

jdfresser/dd-import