A production-grade CLI for managing DefectDojo — list / create / update / delete resources.
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A production-grade CLI for managing DefectDojo — list / create / update / delete every resource the API exposes, plus a fully backward-compatible import path for users coming from the original dd-import tool (now archived).
pip install dd-cli
$ dd --help
Usage: dd [OPTIONS] COMMAND [ARGS]...
Production-grade CLI for managing DefectDojo.
Commands:
configure Interactively create or update a profile.
ping Verify connectivity and authentication against DefectDojo.
config Manage dd-cli profiles and on-disk configuration.
products List and get DefectDojo products.
product-types List and get DefectDojo product types.
engagements List and get DefectDojo engagements.
tests List and get DefectDojo tests.
findings List and get DefectDojo findings.
users List and get DefectDojo users.
dojo-groups List and get DefectDojo authorization groups.
jira-instances List and get DefectDojo Jira instance configurations.
risk-acceptances List and get DefectDojo risk acceptances.
metadata List and get DefectDojo metadata entries.
endpoints List and get DefectDojo endpoints.
finding-templates List and get DefectDojo finding templates.
import Import scanner findings or language data into DefectDojo.
dd-import. Existing CI pipelines that invoke dd-reimport-findings or dd-import-languages with DD_* env vars keep working unchanged. The legacy console scripts are wired as thin shims over the new workflow code.dd configure interactive setup, dd <resource> edit <id> opens the resource as YAML in $EDITOR, action verbs like dd findings close, risk-accept, dd engagements close/reopen.--dry-run previews every mutation without sending HTTP. --yes/-y skips the destructive-op confirmation prompt for scripts. Typed exit codes (auth=3, not-found=5, etc.) so CI can branch on what went wrong.pip install dd-cli
# or, for an isolated install of the CLI:
pipx install dd-cli
dd, dd-reimport-findings, and dd-import-languages go on PATH.
git clone https://github.com/OsamaMahmood/dd-cli.git
cd dd-cli
pip install -e ".[dev,test]"
podman run --rm \
-e DD_URL=https://defectdojo.example.com \
-e DD_API_KEY=… \
ghcr.io/osamamahmood/dd-cli:latest \
ping # or any other dd subcommand
Docker images are published to
ghcr.io/osamamahmood/dd-cli(GitHub Container Registry) andm4rkm3n/dd-cli(Docker Hub) on each tag.
# 1. Set up a profile (writes ~/.config/dd-cli/config.toml)
dd configure
# Profile name [default]: default
# DefectDojo URL: https://defectdojo.example.com
# API key (hidden): …
# Verify TLS certificates? [Y/n]: Y
# 2. Confirm it works
dd ping
# {"ok": true, "user": "alice", "url": "https://defectdojo.example.com"}
# 3. Browse
dd products list --output json | jq
dd findings list --severity Critical --active --output json | jq
# 4. Manage
dd findings close 42 --note "Fixed in v2.1.0" --yes
dd findings risk-accept 51 --until 2026-12-31 --reason "Compensating WAF rule"
dd engagements close 12 --yes
dd users deactivate alice --yes
# 5. Import a scanner report
dd import findings \
--file trivy.json \
--scanner "Trivy Scan" \
--product-type "Web Apps" \
--product "Payments" \
--auto-create
dd-cli resolves settings in this order (later wins):
~/.config/dd-cli/config.toml (or $DD_CLI_CONFIG_DIR/config.toml)DD_* environment variables (legacy contract, see migration)DD_CLI_* environment variables (modern names, take precedence over DD_*)API tokens are stored as pydantic.SecretStr and masked in dd config show output unless you pass --show-secrets to dd config get api_key.
Switch between multiple DefectDojo instances with named profiles:
dd configure --profile prod
dd configure --profile staging
dd config use prod # default profile when --profile isn't given
dd --profile staging products list
Every read command supports --output table|json|yaml (default: table). YAML and JSON are stable and pipe-friendly:
dd findings list --severity High --output json | jq '.[] | {id, title, severity}'
The new ergonomic form:
dd import findings \
--file trivy.json \
--scanner "Trivy Scan" \
--product-type "Web Apps" \
--product "Payments" \
--engagement "Q4 Release" \
--test-name "Trivy" \
[--auto-create | --traditional] \
[--minimum-severity Medium] \
[--push-to-jira] [--close-old-findings] \
[--dry-run] [--yes] [--output table|json|yaml]
Two modes:
--auto-create (recommended) — single API call. DefectDojo creates the product, engagement, and test as needed.--traditional — find-or-create each resource explicitly, then upload. Useful when DefectDojo's auto-create logic disagrees with what you want.Either mode reads the same DD_* env vars the legacy tool used; CLI flags override env vars.
# GitHub Actions
- name: Trivy
run: trivy fs --format json -o trivy.json .
- name: Upload to DefectDojo
env:
DD_URL: ${{ secrets.DD_URL }}
DD_API_KEY: ${{ secrets.DD_API_KEY }}
run: |
pip install dd-cli
dd import findings \
--file trivy.json \
--scanner "Trivy Scan" \
--product-type "Web Apps" \
--product "${{ github.repository }}" \
--engagement "${{ github.ref_name }}" \
--test-name "Trivy" \
--auto-create \
--yes
# GitLab CI
upload_findings:
image: dd-cli:latest
variables:
DD_PRODUCT_TYPE_NAME: "Web Apps"
DD_PRODUCT_NAME: "$CI_PROJECT_NAME"
DD_ENGAGEMENT_NAME: "$CI_COMMIT_REF_SLUG"
DD_TEST_NAME: "Trivy"
DD_TEST_TYPE_NAME: "Trivy Scan"
DD_FILE_NAME: "trivy.json"
DD_AUTO_CREATE_CONTEXT: "true"
script:
- dd-reimport-findings # legacy console script — still works
cloc JSON output for a product:
cloc src --json --out cloc.json
dd import languages --file cloc.json --product-type "Web Apps" --product "Payments"
dd-importdd-cli is a drop-in replacement. Existing pipelines work unchanged — install dd-cli, the legacy console scripts and all DD_* env vars stay valid:
| Legacy | Replacement | Status |
|---|---|---|
dd-reimport-findings | dd-reimport-findings (shim) or dd import findings (new) | both work; DD_* env vars unchanged |
dd-import-languages | dd-import-languages (shim) or dd import languages (new) | both work; DD_* env vars unchanged |
pip install dd-import | pip install dd-cli | new package name |
osamamahmood/dd-import:latest (Docker) | ghcr.io/osamamahmood/dd-cli:latest | swap image, no other changes |
Recommended migration path:
pip install dd-cli) or the Docker image. Pipelines keep working.dd import findings --file …) for --dry-run, typed exit codes, profile support.The new and legacy entry points have one deliberate difference:
dd-reimport-findings exits 1 on any failure (legacy contract — pipelines that grep $? keep working)dd import findings exits with typed codes: 3 (auth), 5 (not found), 6 (validation), 7 (API), 8 (network), 9 (config). Useful for branching CI logic.A full DD_* env-var reference lives in the Configuration guide and is pinned by a 9-test @pytest.mark.compat suite in tests/compat/.
PLAN.md — architecture and roadmapRELEASING.md — how releases are cut and publishedgit clone https://github.com/OsamaMahmood/dd-cli.git
cd dd-cli
pip install -e ".[dev,test]"
make test # 257 unit tests + 12 snapshots
make lint # ruff
make typecheck # mypy --strict
make smoke # 24 integration tests against a live DD (env vars required)
The typed API client in src/dd_cli/_client/ is generated from dd-api.json (DefectDojo's OpenAPI spec). Regenerate after a DefectDojo upgrade:
make install-all # adds openapi-python-client
make generate-client
# review the diff before committing
3-Clause BSD — same as the upstream dd-import project.
dd-cli builds on dd-import by Stefan Fleckenstein at MaibornWolff GmbH, now archived. The original tool's DD_* env-var contract is preserved exactly so existing CI pipelines migrate without changes.
Content type
Image
Digest
sha256:275b51dbb…
Size
57.5 MB
Last updated
5 months ago
docker pull m4rkm3n/dd-cli