Combating Email Hacking Attempts Using AI

I have been doing this for a long time—the whole connectivity game—dating back to the early ‘90s, when networking meant manually cooking router configurations and manual multiplexers for voice and data over PSTN. (Yeah, that was fun.) I’ve witnessed the Slammer worm run amok and the emergence of the concept of zero-trust architecture in the financial world. Now, AI is the hot word, particularly when talking about cybersecurity. And whilst I’m sceptical of any solution which has some AI-powered sticker slapped on it, because 99% of the time it just means we added some automation — with some exceptions — I’ll have to concede on this one as AI is genuinely changing the game of email security.

Email hack isn’t merely about phishing anymore. Attackers are taking advantage of machine learning, generative AI, and automation to create almost perfect impersonation attacks. You know, those old-school rule-based email filters? Completely outmatched. That’s where AI-driven security solutions come into play — and where my team at PJ Networks has been deploying some serious defenses.

Quick Take

If you only want just the highlights:

• Cybersecurity powered by AI can observe trends and anomalies that humans (and simple filters) cannot.
• Machine learning models scour tons of data — email headers, writing style, metadata — to catch suspect emails before they hit your inbox.
• AI-powered solutions are not fail-safe, but they are setting a higher standard against cybercriminals who are also leveraging AI.
• Deploying AI-enhanced email threat detection is a prerequisite, not an option for organizations with a serious approach to security.

How AI Detects Email Threats

Why do you think business email compromise (BEC) has skyrocketed over the years? Attackers got smart. The old signs: typos, funky sender addresses, broken grammar — don’t always hold anymore. Modern phishing emails are so precise and well-written they are sometimes impossible to tell apart from legit emails.

Here’s how AI cybersecurity tools are fighting back:

1. Behavioral Analysis. AI models analyze what is typical email usage for each user and report anything unusual. If at 2 AM the CFO is never sending an email asking for a wire transfer, that gets flagged.
2. Natural Language Processing (NLP). AI doesn’t merely look for emails—it reads material. Sentiment analysis can also be used to identify certain types of scams that contain urgency (URGENT! Transfer funds NOW).
3. Header & Metadata Inspection. AI examines behind-the-scenes elements — IP addresses, time stamps, encryption methods — and catches spoofing and impersonation attempts.
4. Adaptive Learning. AI is different from traditional filters because it evolves. If attackers discover a new tactic, the system learns and adapts without requiring rule updates by hand.

Why does this matter? Because human psychology makes phishing attacks difficult to prevent. That risk is mitigated by AI which identifies malicious emails even before users ever see them.

October 2023 — Machine Learning in Email Security

When I worked as a network admin, we used signature and blacklists to block threats. If an email resembled a known phishing attempt, it received a warning. But that was a game of whack-a-mole — these attackers simply altered a handful of words and, bam, new bypass. Machine learning fixes that. ML models detect patterns in large datasets instead of using a set of explicit lists.

• Supervised Learning: Where it is trained on thousands of known phishing emails, so the AI knows what constitutes a true invoice request, versus a scam.
• Unsupervised Learning: Detects anomalous behavior without needing examples in advance, which is vital to prevent attacks that exploit zero-day vulnerabilities.
• Deep Learning Models: Able to even recognize advanced social engineering tricks via writing style and composition.

Here’s an example: One financial executive at a client’s bank kept receiving emails from her boss. No clear red flags—ID spoofing made it seem legit. Subtle disconnects in writing set off AI-driven filtration, and the email was flagged as a hoax. She could have wired millions out without it. That’s why rules-based security is over—you require protection based on AI and adjusts in real-time.

AI-Powered Threat Protection: The Benefits

Let’s be clear about one thing: AI isn’t going to magically “stop all email hacks.” But it does immensely enhance detection, response, and automation. The biggest advantages:

• Real-time threat detection. Forget manual review by IT teams—AI immediately stops threats in the tracks.
• Lower false positives. What good is a spam filter that catches half your legit mails? AI eliminates needless disruptions.
• Stopping zero-day threats. Every day attackers come up with new tricks — AI readjusts without needing constant manual overhead.
• Context-aware analysis. Most filters flag emails according to keywords. AI knows intent, which translates to fewer missed attacks.
• Automated response & containment AI is capable of quarantining a threat automatically, which can help to stop a malware infection from spreading.

Still using static email security rules to defend against phishing in 2024? They’re playing with fire.

AI-Powered Email Security by PJ Networks

To help combat modern threats with modern defenses, here at PJ Networks, we’ve implemented Fortinet AI-driven email security for our banking and enterprise customers.

What makes it effective?

• Multiple layers of AI detection to identify and stop phishing, BEC scams and malicious attachments.
• Reviews sender activity over time to recognize impersonation attempts.
• Binds into zero-trust architecture (which, by the way, is now a must for financial institutions).
• Automated incident response — AI identifies and quarantines threats before they ever reach users.

More recently, we assisted three banks with tightening their email defenses — one of which faced weekly BEC attempts. Their fraud attempts fell 93% in the first half of the year after they rolled out AI-based security. (Not too shabby for a “system that just looks at emails,” right?)

And look, if I sound worked up about this, it’s because I just returned from DefCon, where I witnessed the sophistication of today’s attacks up close. If banks and enterprises are not leveraging AI for email security, they’re asking for a world of hurt.

Conclusion

Cybersecurity people love to debate about AI — some are true believers, others think it’s overrated. Here’s the thing: AI is not perfect, but it is better than what we have. Static filters and user awareness training alone are reckless when it comes to email threat detection. We’re up against AI-driven attackers. The only way to keep up? AI-powered defense.

And if your business isn’t already using AI-driven email security… what are you waiting for?