OPTOUT

Automated data-broker opt-out engine — top 50 brokers, CCPA/GDPR letters

Privacy / Personal — put individuals back in control of their data.

pip install cognis-optout
optout scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ optout-emit --version
optout 0.1.0

$ optout-emit --help
usage: optout [-h] [--version] [--format {table,json}]
              {brokers,plan,letter} ...

Automated data-broker opt-out engine.

positional arguments:
  {brokers,plan,letter}
    brokers             list known data brokers
    plan                build opt-out requests from a profile
    letter              render a send-ready letter for one broker

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 optout output — reproduce them from a clone.

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

{
"timestamp": "2023-02-15T14:30:00Z",
"findings": [
  {
    "id": "1234567890",
    "title": "Suspicious Network Traffic",
    "description": "Potential malicious activity detected on port 80.",
    "labels": ["network", "suspicious"],
    "objects": [
      {
        "id": "obj-1",
        "type": "indicator",
        "value": "192.0.2.1"
      },
      {
        "id": "obj-2",
        "type": "malware",
        "name": "W32.MyDoom.A"
      }
    ]
  }
]
}

Usage — step by step

optout is an automated data-broker opt-out engine: it builds CCPA/GDPR removal requests from a consumer profile and renders send-ready letters.

1. Install:

   pip install -e .
   optout --version

2. List known data brokers (optionally filtered by regime):

   optout brokers --regime CCPA

3. Build an opt-out plan from a consumer profile JSON:

   optout plan profile.json --regime CCPA

4. Render a send-ready letter for one broker by slug:

   optout letter acxiom profile.json --regime CCPA

5. Automate — emit the plan as JSON, or restrict to specific brokers with --only:

   optout --format json plan profile.json --only acxiom spokeo > plan.json

Contents

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

Why optout?

Automated data-broker opt-out engine — top 50 brokers, CCPA/GDPR letters — without standing up heavyweight infrastructure.

optout 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.

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Features

• ✅ Get Broker
• ✅ Load Profile
• ✅ Render Letter
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

pip install cognis-optout
optout --version
optout scan .                       # scan current project
optout scan . --format json         # machine-readable
optout scan . --fail-on high        # CI gate (non-zero exit)

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Example

$ optout scan .
  [HIGH    ] OPT-001  example finding             (./src/app.py)
  [MEDIUM  ] OPT-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

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Architecture

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

Loading

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Use it from any AI stack

optout is interoperable with every popular way of using AI:

• MCP server — optout mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe optout 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

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How it compares

	Cognis optout	AnalogJ
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 AnalogJ/justvanish, re-framed the Cognis way. Missing a credit? Open a PR.

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Integrations

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

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Install — every way, every platform

pip install "git+https://github.com/cognis-digital/optout.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/optout.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/optout.git" # uv
pip install cognis-optout                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/optout:latest --help        # Docker
brew install cognis-digital/tap/optout                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/optout/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/optout	DEPLOY.md (AWS/Azure/GCP/k8s)

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Related Cognis tools

• recall — Privacy-first local RAG over personal data — encrypted, audit-logged
• vaultmap — Personal asset & account inventory — estate-planning-grade encrypted
• breachwatch — Personal breach aggregator — HIBP + DeHashed + stealer-log triage
• piicomb — Local PII discovery in your own files — SSN/CC/passport/DL/email/phone/DOB
• trackblock — Family phone stalkerware audit — MVT-class iOS/Android forensics
• privacyshell — Hardened browser profile generator — Firefox / LibreWolf / Brave

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

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Contributing

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

⭐ If optout 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 (licensing@cognis.digital). See LICENSE.

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