minfraud
MaxMind minFraud API
Decision gist · record as of 2026-08-14
Yes. Active maintenance, permissive license, low install friction, no known vulnerabilities, and production-stable status make it a solid choice for integrating MaxMind's fraud detection into Python applications. Requires a MaxMind account and API credentials to be useful.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a MaxMind account ID and license key to authenticate requests to the minFraud web service.
- Low install friction with a pure-Python wheel distribution.
- Active maintenance with a release within the last month.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production fraud-detection workflows.
last release 2026-07-21 (24 days) · last repo commit 2026-08-10 · 30 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 106,804 downloads/mo, #12,639 on PyPI
Alternatives
Verify before relying
pip install minfraud
from minfraud import Client
client = Client(account_id=42, license_key='your_key')
response = client.score({'device': {'ip_address': '152.216.7.110'}})- Rate limits or quota constraints on API calls per account tier.
- Latency characteristics for synchronous vs. asynchronous requests in production.
- Specific error recovery and retry behavior for network failures.
What it is and what it does
minfraud is a Python wrapper around MaxMind's minFraud web services for fraud detection and reporting. It provides both synchronous (Client) and asynchronous (AsyncClient) interfaces to query three main services: Score (fast risk assessment), Insights (enriched risk data), and Factors (detailed fraud indicators). The library also supports reporting fraudulent transactions back to MaxMind to improve their detection algorithms.
The package handles request validation before sending to the web service, raising specific exceptions (AuthenticationError, InvalidRequestError, HttpError, InsufficientFundsError) to help you handle different failure modes. It depends on aiohttp and requests for HTTP transport, email-validator and geoip2 for data enrichment, voluptuous for schema validation, and typing-extensions for type hints.
Use it for
- Real-time fraud scoring during checkout to flag high-risk transactions before payment processing.
- Batch analysis of historical transactions to identify patterns and improve internal fraud rules.
- Asynchronous risk assessment in high-throughput payment systems to avoid blocking request handlers.
- Reporting confirmed chargebacks and fraud cases back to MaxMind to strengthen their detection models.
- Enriching transaction logs with geolocation and device risk data for compliance and investigation.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Active maintenance, permissive license, low install friction, no known vulnerabilities, and production-stable status make it a solid choice for integrating MaxMind's fraud detection into Python applications. Requires a MaxMind account and API credentials to be useful.
Install
minfraud on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with a release within the last month. Supports current Python versions (3.10–3.14) and has been maintained since 2015.
Requires a MaxMind account ID and license key to authenticate requests to the minFraud web service.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for most production fraud-detection workflows.
Quickstart
pip install minfraud
from minfraud import Client
client = Client(account_id=42, license_key='your_key')
response = client.score({'device': {'ip_address': '152.216.7.110'}})Verify before relying
- Rate limits or quota constraints on API calls per account tier.
- Latency characteristics for synchronous vs. asynchronous requests in production.
- Specific error recovery and retry behavior for network failures.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesaiohttpemail-validatorgeoip2requeststyping-extensionsvoluptuous |
| Maintenance | Actively maintained 24 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 106,804 / month, #12,639 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: Web EnvironmentIntended Audience :: DevelopersProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: InternetTopic :: Internet :: Proxy ServersTopic :: Internet :: WWW/HTTP |
Evidence: minfraud-3.3.0-py3-none-any.whl
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