Every day, billions of emails move business forward and a few of them bring it to a halt. Despite the rise of advanced security tools and next-gen detection systems, email remains the single most common entry point for malware. In fact, 68% of all malware attacks in 2024 originated via email, and that number is still climbing. Ransomware in particular has evolved from a nuisance attack to one of the most financially devastating forms of cybercrime, with a total cost averaging $5.8 million, according to IBM’s 2025 Cost of a Data Breach Report.

For CISOs, this escalation represents more than a trend, it’s a breaking point for legacy tools. Attackers have learned to weaponize trust, targeting the inbox because it’s where business decisions are made and where human judgment can be most easily exploited.

In a modern business, email is still the primary form of communication, making it both indispensable and inherently vulnerable. Despite new points of entry, cybercriminals continue to infiltrate email as a first step to accessing a larger central data network.

In addition to slipping past gaps in security software, attackers can easily exploit human trust. A message that looks like it’s from a familiar vendor, HR, or finance team can bypass suspicion instantly. Whether it carries a malicious attachment, a link to a fake portal, or a fileless payload, the goal is the same: convince someone to click, download, or act.

And it works. Not because employees are careless, but because today’s threats are designed to look legitimate.

Early malware campaigns were crude but effective, relying on mass spam and simple ransomware to reach as many users as possible. These attacks were noisy, easy to spot, and often opportunistic. But as defenses improved, so did the attackers.

Over time, broad, low-effort campaigns gave way to precision targeting. Phishing emails became more believable, often impersonating known vendors or colleagues to steal credentials and move laterally through connected systems. Instead of solely exploiting software vulnerabilities, attackers began exploiting human ones, using social engineering and contextual cues to make malicious requests seem routine.

Today, that evolution has entered a new phase defined by AI-driven deception. Modern malware adapts in real time, automating reconnaissance and generating endless variations of code that evade traditional detection. Machine learning helps attackers craft messages that match tone, timing, and intent so convincingly that they appear indistinguishable from legitimate communication. Even when one strain is stopped, hundreds of new versions quickly take its place. This constant cycle of adaptation has turned the inbox into a battlefield where speed and precision determine who has the upper hand.

Cyberattacks no longer just lock files or disrupt systems, they halt operations, drain financial resources, and erode customer trust. The financial consequences can be staggering: the FBI’s 2024 IC3 Annual Report found that ransomware losses exceeded $106 million since 2022, and for large enterprises, those costs can multiply quickly when critical systems are affected. But the hidden costs often cut deeper. Downtime stalls productivity and revenue, while reputational damage can linger long after recovery—35% of affected companies report lasting loss of trust.

What makes these attacks so disruptive is how quickly they spread through modern business ecosystems. Malware can move laterally across connected cloud and collaboration tools, turning a single compromised inbox into an enterprise-wide crisis.

Yet, even as threats grow faster and more adaptive, many organizations still rely on defenses built for a simpler era.

Legacy tools like secure email gateways (SEGs) and sandboxes were designed to detect static indicators: malicious files, suspicious links, and known patterns. Today’s attacks rarely leave those behind. Many run entirely in memory, use delayed redirects, or hide behind AI-generated content that looks completely legitimate. These threats exploit behavior, not code, and that means defenses must evolve too.

Protecting the modern business now requires security that understands people as well as payloads—technology capable of learning what normal looks like and spotting the subtle deviations that signal risk.

Behavioral AI brings that visibility into focus. Instead of scanning for known indicators, it learns what “normal” communication looks like—how employees typically interact, when they send messages, what tone they use, and how vendors usually behave. When an anomaly occurs like a supplier suddenly changes a payment account or a colleague emails from an unrecognized domain, it stands out instantly.

By analyzing identity, behavior, and context, this approach detects attacks before the user ever sees them. Unlike rule-based systems that react to threats, behavioral AI anticipates them. It adapts as attackers evolve, closing the gap between unseen risks and actionable defense.

Email will continue to be where business happens and where attackers will seek their advantage. The difference now lies in how we defend it. Protecting the inbox means understanding the people behind it: how they communicate, who they trust, and what normal behaviour looks like.

With the right intelligence, organizations can move from reacting to incidents to anticipating them, combining human-aware behavioural insight with machine-speed detection to stop threats before they reach the user.

That’s the foundation of Abnormal’s approach and the focus of our latest research. To learn how behavioural AI helps security leaders transform unseen risks into measurable resilience, read the CISO Guide to Malware and Ransomware.

The inbox may still rule, but that doesn’t mean it has to be the weak link.