Txgraph

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ txgraph-emit --version
txgraph 0.1.0

$ txgraph-emit --help
usage: txgraph [-h] [--version] COMMAND ...

Build a transaction graph and surface AML structuring / layering / mule patterns from a CSV.

positional arguments:
  COMMAND
    scan      Scan a transaction CSV for suspicious patterns.

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

Command-line interface for TXGRAPH.

Examples:
  # Scan a CSV and print a findings table
  txgraph scan demos/01-basic/transactions.csv

  # Emit JSON for a CI gate (exits non-zero when findings exist)
  txgraph scan transactions.csv --format json > findings.json

  # Print the SAR narrative
  txgraph scan transactions.csv --sar

  # Custom structuring threshold
  txgraph scan transactions.csv --threshold 5000

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

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

{
"tx_id": "1234567890",
"findings": [
    {
        "id": "finding-1",
        "title": "Suspicious Network Traffic",
        "description": "Network traffic from unknown IP address",
        "severity": "high"
    },
    {
        "id": "finding-2",
        "title": "Unusual File Access",
        "description": "File access from unauthorized user",
        "severity": "medium"
    }
]
}

Usage — step by step

1. Install (Python 3.9+):

   pip install txgraph
   

2. Scan a transaction CSV for AML patterns (structuring, layering, etc.):

   txgraph scan transactions.csv
   

3. Tune detection. Set the structuring report threshold and choose which severity should fail the run:

   txgraph scan transactions.csv --threshold 10000 --fail-on high
   

4. Read the output. Emit JSON for tooling, or print the SAR narrative for an analyst:

   txgraph scan transactions.csv --format json | jq '.findings[]'
   txgraph scan transactions.csv --sar
   

5. Gate in CI. With --fail-on, the exit code is non-zero when matching findings exist:

   txgraph scan transactions.csv --fail-on any || echo "AML findings detected"
   

Contents

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

Why txgraph?

Graph-based money-laundering detection is academically hot but has no plug-and-play CLI; ingest CSV, emit suspicious subgraphs + SAR-ready summaries with zero infra is a viral AML demo.

txgraph 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

• ✅ Load Transactions
• ✅ Build Graph
• ✅ Detect Structuring
• ✅ Detect Layering
• ✅ Detect Mules
• ✅ Analyze
• ✅ Sar Summary
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[addresses + transactions] --> P[txgraph<br/>cluster + trace]
  P --> OUT[sanctions xref / report]

Use it from any AI stack

txgraph is interoperable with every popular way of using AI:

• MCP server — txgraph mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe txgraph 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 txgraph	AMLSim
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 AMLSim / Neo4j fraud graph, 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 (txgraph 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/txgraph.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/txgraph.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/txgraph.git" # uv
pip install cognis-txgraph                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/txgraph:latest --help        # Docker
brew install cognis-digital/tap/txgraph                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/txgraph/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/txgraph	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 txgraph 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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