Email attacks are no longer arriving as obvious spam or malware. Some attacks contain no malicious attachment; rather, they rely on trust, urgency, payment context, and normal business behavior. For instance, a convincing message may imitate an executive, use a supplier’s compromised account, continue an existing conversation, or persuade an employee to send sensitive information to the wrong person.
Threat intelligence often has a slightly glamorous (and serious) association with spying and national security activities. In email security, however, it’s slightly unglamorous; mostly involving the use of threat data, behavioral signals, sender context, domain reputation, message patterns, and recipient activity to judge whether an email is safe, suspicious, or dangerous.
Email attacks are now built around timing. A phishing email does not need to sit in an inbox for days to create damage. A user can click in minutes, a finance team can act on a fake vendor request before anyone checks the sender, a malicious link can look harmless at delivery and turn dangerous later, or a reply can come from a compromised account inside a trusted thread and bypass the usual suspicion that comes with a new sender.
Most cyberattacks don’t look malicious anymore; rather, they’re as normal as they can be. An email arrives from a known vendor, the tone matches past conversations, the timing aligns with an active transaction... Nothing triggers suspicion until money moves or data leaks.
Enterprises already know that the inbox is one of the easiest ways for attackers to get into the business. The real question is narrower: when vendors say they use AI-based email security, what actually changes compared with rule-based, traditional email security?
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