How do mailbox providers identify phishing patterns?

Machine learning models analyze message characteristics associated with **phishing**: linguistic patterns, sender behavior, link characteristics, and structural elements. Models train on confirmed **phishing** and legitimate messages.

User feedback provides training data. When users mark messages as **phishing**, that signal informs detection models. Aggregated reporting across millions of users reveals campaign patterns quickly.

Threat intelligence integration adds external signals: known **phishing** URLs, campaign fingerprints, and emerging attack patterns. Real-time feeds enable rapid response to new threats before they spread widely.