Unmasking BEC attacks using Natural Language Understanding + MQL

Business Email Compromise (BEC) attacks are sophisticated cybercrimes targeting organizations of all sizes by impersonating trusted figures to trick employees into unauthorized transactions or revealing sensitive information. These attacks are challenging to detect with traditional security measures due to their customized nature and the absence of typical malicious payloads. Advanced technologies like Natural Language Understanding (NLU) offer a powerful defense by analyzing email content to identify potential threats through intent classification and Named Entity Recognition (NER). By integrating NLU with Message Query Language (MQL), organizations can rapidly adapt their defenses against BEC attacks by identifying deceptive language patterns and suspicious signals, such as impersonation or urgency. This comprehensive approach enhances the security of digital environments, protecting organizations from financial and reputational harm caused by cyber threats.