Dpiaforge

pip install cognis-dpiaforge

dpiaforge scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ dpiaforge-emit --version
dpiaforge 0.1.0

$ dpiaforge-emit --help
usage: dpiaforge [-h] [--version] [--format {table,json}] {assess} ...

DPIA & EU AI Act impact-assessment generator (offline, stdlib-only).

positional arguments:
  {assess}
    assess              run full DPIA + AI Act assessment on an activity JSON

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}
                        output format (default: table)

Blocks above are real dpiaforge output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Traffic",
        "description": "Anomalous network traffic detected from IP 192.168.1.100.",
        "created_by": "John Doe",
        "created_at": "2023-02-15T14:30:00Z"
    },
    {
        "id": "2345678901",
        "title": "Malware Detection",
        "description": "Malware detected on system with IP 192.168.1.101.",
        "created_by": "Jane Smith",
        "created_at": "2023-02-16T10:45:00Z"
    }
]
}

Usage — step by step

1. Install the CLI:

   pip install dpiaforge
   

2. Assess a processing activity described in a JSON file (or - for stdin) for DPIA + EU AI Act risk:

   dpiaforge assess activity.json
   

3. Pipe the activity in from another step:

   cat activity.json | dpiaforge assess -
   

4. Read the output. The global --format json flag emits a machine-readable assessment:

   dpiaforge --format json assess activity.json > dpia.json
   

5. Wire it into CI / governance automation — regenerate the assessment whenever the activity record changes:

   dpiaforge --format json assess activity.json > artifacts/dpia.json || exit 1
   

Contents

• Why dpiaforge? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why dpiaforge?

AI governance wave

dpiaforge is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Dpia Threshold

• ✅ Classify Ai Act Tier

• ✅ Risk Score

• ✅ Assess

• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer

• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-dpiaforge

dpiaforge --version

dpiaforge scan .                       # scan current project

dpiaforge scan . --format json         # machine-readable

dpiaforge scan . --fail-on high        # CI gate (non-zero exit)

Example

$ dpiaforge scan .

  [HIGH    ] DPI-001  example finding             (./src/app.py)

  [MEDIUM  ] DPI-002  another signal              (./config.yaml)



  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[input] --> P[dpiaforge<br/>analyze + score]
  P --> OUT[report]

Use it from any AI stack

dpiaforge is interoperable with every popular way of using AI:

• MCP server — dpiaforge mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)

• OpenAI-compatible / JSON — pipe dpiaforge scan . --format json into any agent or LLM

• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line

• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

| | Cognis dpiaforge | EU AI Act tooling |

|---|:---:|:---:|

| Self-hostable, no account | ✅ | varies |

| Single command, zero config | ✅ | ⚠️ |

| JSON + SARIF for CI | ✅ | varies |

| MCP-native (AI agents) | ✅ | ❌ |

| Polyglot ports (JS/Go/Rust) | ✅ | ❌ |

| Open license | ✅ COCL | varies |

Built in the spirit of EU AI Act tooling, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (dpiaforge mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/dpiaforge.git"    # pip (works today)

pipx install "git+https://github.com/cognis-digital/dpiaforge.git"   # isolated CLI

uv tool install "git+https://github.com/cognis-digital/dpiaforge.git" # uv

pip install cognis-dpiaforge                                          # PyPI (when published)

docker run --rm ghcr.io/cognis-digital/dpiaforge:latest --help        # Docker

brew install cognis-digital/tap/dpiaforge                             # Homebrew tap

curl -fsSL https://raw.githubusercontent.com/cognis-digital/dpiaforge/main/install.sh | sh

| Linux | macOS | Windows | Docker | Cloud |

|---|---|---|---|---|

| scripts/setup-linux.sh | scripts/setup-macos.sh | scripts/setup-windows.ps1 | docker run ghcr.io/cognis-digital/dpiaforge | DEPLOY.md (AWS/Azure/GCP/k8s) |

Related Cognis tools

• soc2box — SOC 2 evidence collector and control tracker, self-hosted

• gdprkit — GDPR/CCPA DSAR, RoPA, and cookie-consent toolkit

• policyforge — Auto-generate security policies from a short questionnaire

• vendorvet — Third-party / vendor risk questionnaires with SBOM cross-ref

• auditrail — Tamper-evident audit-log aggregator with hash-chained attestation

• frameworkmap — Crosswalk controls across NIST, ISO 27001, SOC 2, CMMC, PCI

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If dpiaforge saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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