dd-cli 2.0.0rc1

Production-grade CLI for managing DefectDojo

dd-cli

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.

Why dd-cli

• Complete API coverage. Every read and write across 12 DefectDojo resource types — products, product-types, engagements, tests, findings, users, dojo-groups, jira-instances, risk-acceptances, metadata, endpoints, finding-templates — driven from a typed client generated from DefectDojo's OpenAPI spec.
• Drop-in replacement for 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.
• Pleasant interactive use. Rich tables, JSON / YAML output for piping, profiles for switching between DefectDojo instances, 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.
• Safe writes. --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.
• Validated against real DefectDojo. 24 integration tests run against a live instance per release, including a full Trivy-report import round-trip.

Install

From PyPI (recommended)

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.

From source

git clone https://github.com/OsamaMahmood/dd-cli.git
cd dd-cli
pip install -e ".[dev,test]"

Docker

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 and osamamahmood/dd-cli on each tag. Until those land in M5b, build locally: podman build -t dd-cli .

Quickstart

# 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

Configuration

dd-cli resolves settings in this order (later wins):

1. Built-in defaults
2. The active profile in ~/.config/dd-cli/config.toml (or $DD_CLI_CONFIG_DIR/config.toml)
3. DD_* environment variables (legacy contract, see migration)
4. DD_CLI_* environment variables (modern names, take precedence over DD_*)
5. Explicit CLI flags

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.

Profiles

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

Output formats

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}'

Importing scanner findings

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.

From CI/CD

# 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

Importing language statistics

cloc JSON output for a product:

cloc src --json --out cloc.json
dd import languages --file cloc.json --product-type "Web Apps" --product "Payments"

Migrating from dd-import

dd-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:

1. Today: swap the install command (pip install dd-cli) or the Docker image. Pipelines keep working.
2. When convenient: migrate to the new ergonomic commands (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 docs/configuration.md (in M5b3) and is pinned by a 9-test @pytest.mark.compat suite in tests/compat/.

Documentation

• PLAN.md — architecture and roadmap
• RELEASING.md — how releases are cut and published
• docs/ — full user guide (in M5b3)

Development

git 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

License

3-Clause BSD — same as the upstream dd-import project.

Acknowledgments

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.