How do anti-abuse networks detect compromised senders?

Detection combines automated analysis with human investigation. Sudden sending pattern changes, **spam trap** hits, complaint spikes, and content fingerprinting identify potentially compromised accounts or infrastructure.

Behavioral signals include: sending to addresses never contacted before, unusual volume spikes, content inconsistent with historical patterns, and sending during atypical hours. These suggest account compromise rather than legitimate sender behavior change.

Networks share compromise indicators to accelerate detection across the ecosystem. Once one network identifies a compromised pattern, others can detect similar compromises faster. This collaborative detection helps contain abuse spread.