How do filters adapt to emerging spam tactics?

Filters adapt to emerging spam tactics through continuous learning from new examples, adversarial training, and monitoring for distribution shift. When spammers develop new techniques, the resulting messages generate user complaints that feed back into model training.

Adversarial training specifically prepares models for evasion attempts by including examples designed to bypass filters. Security researchers generate adversarial examples to probe filter weaknesses, then train models to handle these attack patterns.

Distribution monitoring detects when incoming mail characteristics shift from training data patterns, signaling potential new spam tactics or changes requiring investigation. Automated alerts trigger human review when anomalies appear, enabling rapid response to novel threats.