Abuse email detection typically involves a combination of techniques: - Content analysis: Checking emails for suspicious links, attachments, and keywords that are commonly associated with spam or phishing. - Behavioral analysis: Monitoring sending patterns, such as the rate of emails sent and the number of bounces or complaints received. - Reputation scores: Using third-party services to assess the sender's reputation based on historical data and feedback from recipients. - Machine learning: Employing algorithms that can learn from past data to identify new patterns of abuse.