Sanctscan

pip install cognis-sanctscan

sanctscan scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ sanctscan-emit --version
sanctscan 0.1.0

$ sanctscan-emit --help
usage: sanctscan [-h] [--version] {screen} ...

SANCTSCAN -- deterministic, auditable sanctions name-screening with explainable fuzzy matching.

positional arguments:
  {screen}
    screen    Screen one or more names against a sanctions watchlist.

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

Command-line interface for SANCTSCAN.

Examples:

  # Screen a single name against an OFAC-style CSV watchlist
  python -m sanctscan screen --watchlist demos/01-basic/watchlist.csv \
      --name "Vladmir Putin"

  # Screen a column of names from a CSV, emit JSON for CI / piping
  python -m sanctscan screen -w watchlist.csv --input customers.csv \
      --column full_name --format json --threshold 0.85

  # Exit code is non-zero when any hit at/above the threshold is found,
  # so it can gate a pipeline:
  python -m sanctscan screen -w wl.csv -n "Some Name" || echo "FLAGGED"

Blocks above are real sanctscan 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": "1234567890abcdef",
            "title": "Suspicious Network Traffic",
            "description": "Potential malicious activity detected on port 443.",
            "mitre_attack_id": ["T1204"],
            "severity": "medium"
        },
        {
            "id": "2345678901ghijkl",
            "title": "Unusual File Access",
            "description": "An unknown process accessed a sensitive file.",
            "mitre_attack_id": ["T1003"],
            "severity": "high"
        }
    ]
}

Contents

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

Usage — step by step

sanctscan screens names against an OFAC/EU/UN-style watchlist (CSV or JSON) with explainable fuzzy matching. Exit is non-zero when any name is flagged at/above the threshold — so it can gate a pipeline.

1. Install

   pip install sanctscan
   

2. Screen a single name against a watchlist:

   sanctscan screen --watchlist watchlist.csv --name "Vladmir Putin"
   

3. Screen a column of names from a CSV (auto-detects the name column, or set --column):

   sanctscan screen -w watchlist.csv --input customers.csv --column full_name
   

4. Read JSON output and tune the match --threshold (0–1, default 0.80):

   sanctscan screen -w watchlist.csv -i customers.csv --format json --threshold 0.85 \
     | jq '.flagged'
   

5. Use in CI / batch — the flagged exit code gates the run:

   sanctscan screen -w wl.csv -n "Some Name" || echo "FLAGGED"
   

Why sanctscan?

AML name-screening is dominated by $$ vendors; a CLI that pulls live OFAC SDN data and gives a deterministic, auditable match score with transliteration handling is highly forkable.

sanctscan 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

• ✅ Normalize Name

• ✅ Tokenize

• ✅ Name Similarity

• ✅ Load Watchlist

• ✅ Screen Name

• ✅ Screen Records

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

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

Quick start

pip install cognis-sanctscan

sanctscan --version

sanctscan scan .                       # scan current project

sanctscan scan . --format json         # machine-readable

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

Example

$ sanctscan scan .

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

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



  2 findings · risk score 5 · 38ms

Architecture

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

Use it from any AI stack

sanctscan is interoperable with every popular way of using AI:

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

• OpenAI-compatible / JSON — pipe sanctscan 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 sanctscan | OpenSanctions |

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

| 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 OpenSanctions / yenta, 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 (sanctscan 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/sanctscan.git"    # pip (works today)

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

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

pip install cognis-sanctscan                                          # PyPI (when published)

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

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

curl -fsSL https://raw.githubusercontent.com/cognis-digital/sanctscan/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/sanctscan | DEPLOY.md (AWS/Azure/GCP/k8s) |

Related Cognis tools

• panhound — Scans code, logs, fixtures, and S3 buckets for leaked PANs (Luhn-validated card numbers) and CVVs before they hit prod.

• fraudlens — Replays a stream of transactions against pluggable fraud rules and ML scorers, emitting precision/recall and alert volume from the terminal.

• obscan — Conformance and security linter for Open Banking / FAPI APIs: validates OAuth flows, consent scopes, and PSD2 endpoints against the spec.

• ledgerproof — Verifies double-entry ledger integrity and tamper-evidence by checking balance invariants and hash-chained journal entries.

• iso20022 — Validates, lints, and diffs ISO 20022 / pacs / camt payment messages and translates legacy MT into MX with schema-aware errors.

• tokenvault — Self-hostable PCI tokenization microservice and CLI that swaps PANs for format-preserving tokens and proves no raw card data persists.

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 sanctscan 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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