Privacyshell

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ privacyshell-emit --version
privacyshell 0.1.0

$ privacyshell-emit --help
usage: privacyshell [-h] [--version] [--format {table,json}]
                    {generate,audit,list} ...

Hardened browser profile generator (Firefox/LibreWolf/Brave).

positional arguments:
  {generate,audit,list}
    generate            generate a hardened profile
    audit               audit an existing user.js file
    list                list available browsers and profiles

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

$ privacyshell-emit list
{
  "browsers": [
    "firefox",
    "librewolf",
    "brave"
  ],
  "profiles": [
    "balanced",
    "hardened",
    "paranoid"
  ]
}

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

Usage — step by step

1. Install the CLI (Python 3.9+):

   pip install git+https://github.com/cognis-digital/privacyshell.git
   

2. List the available browsers and hardening profiles:

   privacyshell list
   

3. Generate a hardened profile (e.g. a Firefox user.js):

   privacyshell generate --browser firefox --profile hardened --emit userjs > user.js
   

4. Audit an existing user.js against a profile (read JSON / exit code):

   privacyshell --format json audit user.js --browser firefox --profile hardened
   

5. Enforce the hardening baseline in CI:

   - name: audit browser hardening
     run: |
       pip install git+https://github.com/cognis-digital/privacyshell.git
       privacyshell --format json audit user.js
   

Contents

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

Why privacyshell?

Hardened browser profile generator — Firefox / LibreWolf / Brave — without standing up heavyweight infrastructure.

privacyshell 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

• ✅ Build Profile
• ✅ Render Userjs
• ✅ Render Brave Policy
• ✅ Audit Userjs
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[target / manifest] --> P[privacyshell<br/>checks + rules]
  P --> OUT[findings (JSON / SARIF)]

Use it from any AI stack

privacyshell is interoperable with every popular way of using AI:

• MCP server — privacyshell mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe privacyshell 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 privacyshell	arkenfox
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 arkenfox/user.js, 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 (privacyshell 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/privacyshell.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/privacyshell.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/privacyshell.git" # uv
pip install cognis-privacyshell                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/privacyshell:latest --help        # Docker
brew install cognis-digital/tap/privacyshell                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/privacyshell/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/privacyshell	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• recall — Privacy-first local RAG over personal data — encrypted, audit-logged
• optout — Automated data-broker opt-out engine — top 50 brokers, CCPA/GDPR letters
• 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

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 privacyshell 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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