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Eye on AI

#313 Evan Reiser: How Abnormal AI Protects Humans with Behavioral AI

49 min episode · 2 min read
·
Evan Reiser

Episode

49 min

Read time

2 min

Topics

Career Growth, Fundraising & VC, Design & UX

AI-Generated Summary

Key Takeaways

  • Behavioral Security Approach: Abnormal creates behavior models of every enterprise employee by integrating with IT systems, analyzing emails against known good patterns rather than known bad threats, achieving 2-10x better detection than conventional threat intelligence methods.
  • AI-Powered Attack Evolution: Criminals use ChatGPT and open-source LLMs to generate hyper-personalized phishing emails at scale, researching targets via LinkedIn and web pages, crafting messages that reference past conversations and personal details, making attacks indistinguishable from legitimate communication.
  • Vendor Account Compromise: Attackers breach small vendors with weak security, access their email history, then use LLMs to analyze thousands of past emails and automatically generate convincing payment requests to all customers using real account numbers and personal references.
  • AI Transformation Strategy: Abnormal implements AI across four business processes—product development, employee lifecycle, customer journey, sales/marketing—achieving 10x improvements in engineering through automated bug fixing, AI-generated designs, and 24-hour resolution cycles versus traditional development timelines.

What It Covers

Evan Reiser explains how Abnormal AI uses behavioral modeling to detect sophisticated email attacks that bypass traditional security, protecting 25% of Fortune 500 companies from social engineering threats costing billions annually.

Key Questions Answered

  • Behavioral Security Approach: Abnormal creates behavior models of every enterprise employee by integrating with IT systems, analyzing emails against known good patterns rather than known bad threats, achieving 2-10x better detection than conventional threat intelligence methods.
  • AI-Powered Attack Evolution: Criminals use ChatGPT and open-source LLMs to generate hyper-personalized phishing emails at scale, researching targets via LinkedIn and web pages, crafting messages that reference past conversations and personal details, making attacks indistinguishable from legitimate communication.
  • Vendor Account Compromise: Attackers breach small vendors with weak security, access their email history, then use LLMs to analyze thousands of past emails and automatically generate convincing payment requests to all customers using real account numbers and personal references.
  • AI Transformation Strategy: Abnormal implements AI across four business processes—product development, employee lifecycle, customer journey, sales/marketing—achieving 10x improvements in engineering through automated bug fixing, AI-generated designs, and 24-hour resolution cycles versus traditional development timelines.

Notable Moment

A bank CISO warns that future AI attacks may involve undetectable cultural biases embedded in models, subtly shifting employee values over years toward socialism or other ideologies without observable short-term indicators, representing warfare beyond current detection capabilities.

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Episode Transcript

Let's have you introduce yourself. Tell us how you got to abnormal.ai and what Abnormal does, and then we'll talk about the current threat landscape. Sounds great. Well, first of all, Craig, thank you so much for having me on the show. My name is Evan Reiser. I'm the founder and CEO of Abnormal Security, which is now called Abnormal AI. And, you know, my background is not in cybersecurity. I spent the grand majority of my career getting people to click on ads. So if you imagine all those annoying you know, there's companies that maybe, you know, suck up some of your data and fall around the Internet with ads showing you things you looked at on different websites. That's almost certainly my fault at some level, so I apologize. And now trying to fight back a little bit by, you know, stopping some crime and putting bad guys in jail. So I'm a bit of a cybersecurity outsider, but I've been an AI insider for a long time. As you probably know, you know, behavioral ad targeting, it's all about looking at large sets of data, understanding, you know, creating behavioral models of people, trying to understand, you know, what they do when they're exposed to different types of stimulus. So that's kinda how I got I got into cybersecurity just through, honestly, like, lovely technology. I've worked in AI for a long time. I saw the technology, obviously, getting way better even seven or eight years ago. It's changed a lot in the last, you know, twenty years. Even last, you know, two months, it's changed. So the idea for Abnormal was actually not really an email security company. That's what we're most known for today. It was really create a behavioral security platform that could basically understand humans' identities better than humans and then predict their behavior. And the idea if we idea was if we could do that, we could probably help businesses and, you know, stop some crime. We started with email because, you know, it was it's phishing is the number one cause of breaches. Business email compromise is the number one cause of financial loss in the enterprise. And a lot of the conventional solutions are overly reliant on threat intelligence, different signatures, patterns, and heuristics. And what we see, especially in the age of AI and, you know, due to very, you know, sophisticated criminals, there's new attacks every day. They're personalized. They're targeted. There's a lot of social engineering. Those things you know, every attack's unique. You can't use some of the conventional, you know, techniques. So rather than kind of studying known bad, we focus on known good. We create behavior models of every person in the enterprise by integrating directly into the IT systems. And then when a new email comes in or, you know, other activities happen for other products, we analyze it to say, you know, is it risky, and is it normal, and does …

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    Criminals use ChatGPT and open-source LLMs to generate hyper-personalized phishing emails at scale, researching targets via LinkedIn and web pages.

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  • Evan Reiser explains how Abnormal AI uses behavioral modeling to detect sophisticated email attacks that bypass traditional security, protecting 25% of Fortune 500 companies from social engineering threats.

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