One of the most difficult challenges of building an effective ML system to prevent email attacks is keeping up with the rapidly changing and adversarial nature of the problem. Attackers are constantly
In this article, we discuss how, on top of our probabilistic data-science based detection engine, Abnormal also employs signatures as a “safety net” to catch known attacks or known false positives that
Stopping advanced social engineering is a tough AI problem. Because these attacks are so rare and carefully created to fool not only humans, but also machines, we must deeply understand the attacker’s
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