Meilleur filtre de protection contre le spam électronique - Tutoriel 2026
Empêchez le spam, le phishing, les logiciels malveillants, le blocage des publicités, les trackers de pixels et bien plus encore pour les formulaires de contact et les serveurs de messagerie.
A spam filter for Node.js, the command line and mail servers. It catches spam, phishing, scams and malware in any language, explains every decision, and can ask a language model about close calls.
spamscanner.net · Getting started · Documentation
Install
npm install --global spamscanner # the command line
npm install spamscanner # the library
Or a standalone binary, with nothing else to install:
curl -fsSL https://github.com/spamscanner/spamscanner/releases/latest/download/install.sh | bash
The package needs Node.js 18 or later.
Use
spamscanner scan message.eml
SPAM score 16.3 (spam at 5.0, reject at 15.0) action: reject language: en
+6.3 BAYES_999 Classifier spam probability 99.9%
+5.0 PHISHING_LOOKALIKE_DOMAIN "paypa1-secure.top" imitates paypal by swapping characters
+3.0 DECEPTIVE_LINK A link shows "https://www.paypal.com/signin" but goes to paypa1-secure.top
+2.0 FROM_NAME_BRAND Display name says "paypal" but the message is from paypa1-secure.top
import SpamScanner from 'spamscanner';
const scanner = new SpamScanner();
const result = await scanner.scan(rawMessage, {
session: {remoteAddress: '203.0.113.5', envelope: {rcptTo: [{address: 'bob@example.org'}]}},
});
result.isSpam; // true
result.action; // 'accept', 'tag' or 'reject'
result.tests; // [{name: 'DECEPTIVE_LINK', score: 3, description: '...'}, ...]
With Postfix:
spamscanner milter --port 7831 --auth --subject-tag "[SPAM]"
sudo postconf -e smtpd_milters=inet:127.0.0.1:7831 milter_default_action=accept
sudo postfix reload
With a local language model:
ollama pull qwen3.5:4b
spamscanner scan message.eml --llm ollama --llm-model qwen3.5:4b
Documentation
- Getting started
- Command line
- Postfix and Sendmail, other mail servers, HTTP API and spamd
- How it works, tests and scores, languages
- Language models, with recommended open models from Hugging Face
- Training
- Forward Email, and upgrading from version 5 or 6
- API reference
- Security and privacy
The same pages are in docs/ in this repository. The website and documentation are also in 24 other languages; see i18n/.
Development
npm install
npm test # lint, build, and every test, with 100% coverage required
npm run test:e2e # end-to-end tests against Postfix, ClamAV, spamc and Ollama; see test/e2e/
npm run model:train # rebuild the bundled model from public datasets
npm run site:build # build spamscanner.net into _site/
npm run site:serve # preview it at http://localhost:8080
npm run i18n:check # check the translations against the English pages