Piicomb

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ piicomb-emit --version
piicomb 2.0.0

$ piicomb-emit --help
usage: piicomb [-h] [--version] {scan,redact,recognizers} ...

Local PII discovery for your own files: SSN/ITIN/EIN, credit cards (Luhn),
IBAN (mod-97), passport, driver license, email, phone, IPv4/IPv6/MAC, DOB,
ZIP+4, and high-entropy API secrets, with context-word confidence boosting.

positional arguments:
  {scan,redact,recognizers}
    scan                discover PII in a path
    redact              print a file with PII masked
    recognizers         list bundled recognizers

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit

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

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

{
  "incident": {
    "id": "1234567890",
    "created_at": "2023-02-20T14:30:00Z",
    "updated_at": "2023-02-20T14:30:00Z"
  },
  "observables": [
    {
      "type": "ip-dst",
      "value": "192.0.2.1/32",
      "description": "Potential attacker IP address"
    }
  ],
  "indicators": [
    {
      "type": "url",
      "value": "https://example.com/malware.exe",
      "description": "Malicious URL download"
    }
  ]
}

Usage — step by step

1. Install the CLI (Python 3.9+):

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

2. List the bundled recognizers so you know which labels you can target:

   piicomb recognizers
   

3. Scan a file or directory for PII:

   piicomb scan ./data
   

4. Narrow recognizers / confidence and emit JSON, or print a masked copy:

   piicomb scan ./data --only EMAIL,IPV4 --min-score 0.6 --format json
   piicomb redact notes.txt
   

5. Gate CI on any discovered PII:

   - name: pii comb
     run: |
       pip install git+https://github.com/cognis-digital/piicomb.git
       piicomb scan . --fail-on-find
   

Contents

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

Why piicomb?

Local PII discovery in your own files — SSN/CC/passport/DL/email/phone/DOB — without standing up heavyweight infrastructure.

piicomb 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

• ✅ Luhn Ok
• ✅ Valid Ssn
• ✅ Valid Card
• ✅ Valid Dob
• ✅ Redact Text
• ✅ Scan Text
• ✅ Scan File
• ✅ Scan Path
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[target / export] --> P[piicomb<br/>collect + correlate]
  P --> OUT[ranked findings]

Use it from any AI stack

piicomb is interoperable with every popular way of using AI:

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

Contributing

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

⭐ If piicomb 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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