--- title: The One-Shot Phishing Attack: Adversarial AI and the New Rules of Social Engineering source_page: https://www.sardine.ai/media/fraudology/episodes/adversarial-ai canonical: https://www.sardine.ai/media/fraudology/episodes/adversarial-ai format: text/markdown date: 2026-08-20T04:01:00.000Z description: Adversarial AI is making phishing and social engineering cheaper, faster, and more convincing. Fraud and cybersecurity teams must adapt alongside the attacks… --- **Quick links:** [Human page](https://www.sardine.ai/media/fraudology/episodes/adversarial-ai) · [Home](https://www.sardine.ai) · [Customers](https://www.sardine.ai/customers) · [Blog](https://www.sardine.ai/blog) · [Demo](https://www.sardine.ai/demo) --- # The One-Shot Phishing Attack: Adversarial AI and the New Rules of Social Engineering **Published:** 2026-08-20T04:01:00.000Z Adversarial AI is making phishing and social engineering cheaper, faster, and more convincing. Fraud and cybersecurity teams must adapt alongside the attacks… Welcome back to Fraudology. I have to tell you I’m genuinely excited about this one. Today’s guest was highly recommended by Matt Vega, someone whose opinion I trust completely in this industry. By the time we finally hit record, we’d already been talking for 45 minutes off air. That’s a pretty good sign this episode is going to deliver. Cy Khormaee spent years at Google, building out what eventually became the company’s user protection platform and the technology that now runs quietly in the background protecting billions of devices worldwide from phishing and malware. He took that experience and eventually founded Aegis.AI, and he just got back from Black Hat, which means he is walking into this conversation with a front-row view of exactly where adversarial AI is heading next. What I wasn’t fully prepared for was how far he was willing to take the demonstration. Cy didn’t just tell me adversarial AI is a growing thread, he showed me, live. Using nothing more than ChatGPT and information freely available online. It’s the kind of moment that changes how you think about a threat you thought you already understood. We cover a lot of ground in this one. And if you work in fraud, trust and safety, or security in any capacity, this is one you’ll want to sit with. What you’ll hear in this episode: Cy's path from Google's user protection platform, home of reCAPTCHA and Safe Browsing, to founding Aegis.AI, and how credential stuffing defense evolved into a hundred-million-dollar business. A live ChatGPT phishing demo where Cy used open source intelligence to research himself and generate a convincing, contextualized phishing email and matching fake conference website in minutes. Why AI phishing attacks have moved from theoretical to fully operational, with real-world state actor phishing tactics now automatable at near-zero cost. The staggering AI phishing email bypass rate statistics: over 50% of emails now slip past existing security email filter bypass controls. Why AI red team fraud thinking, treating AI as a gardener to nurture rather than a carpenter to micromanage, changes how fraud and security teams should actually deploy these tools. How the real Robinhood phishing attack shows why login fraud detection signals and upstream fraud detection AI matter more than ever. Why fraud and cybersecurity convergence isn't optional anymore, and how fraud data sharing across teams closes gaps that adversaries are actively exploiting. How automated sandboxing fraud detection can catch attacks before a user ever clicks, and why carding attack prevention and account takeover detection increasingly rely on the same signals as cybersecurity teams. You should listen to this episode if you: Work in fraud, trust and safety, or security and want to understand how adversarial AI is changing social engineering and phishing attacks. Are responsible for account takeover detection, credential stuffing detection, or synthetic identity risk at a bank, fintech, or merchant. Assumed business email compromise had been mostly solved and need a reality check. Are evaluating AI fraud investigation automation tools and want a clearer sense of what can realistically be automated today. Are trying to build the case internally for fraud and cybersecurity convergence and fraud data sharing across teams. ### Episode notes From Google Safe Browsing to Aegis.AI Cy’s path into fraud and security started almost by accident. He landed on Google’s reCAPTCHA and Safe Browsing team, helping to turn an internal security tool into a business protecting billions of devices worldwide. That background, plus a stint helping fraud-fighting tools with Matt Vega during his Instacart days, sets up everything that follows in this conversation. The ChatGPT phishing demo Cy walks through a live demonstration of using ChatGPT with zero specialized tools to research himself using open source intelligence. He then generates a tailored phishing email disguised as a speaker conference confirmation, complete with a cloned fake website. It’s what Cy calls “one-shotting your way to being a fraudster.” and it shows how low the skill floor has dropped for AI phishing attacks. Why the old defenses are failing Cy shares a striking data point that the average email now has better than a coin-flip chance of bypassing existing security filters. Combined with a real example from the Robinhood phishing attack, where a compromised marketing server sent fully legitimate-looking emails from real infrastructure, this section makes the case that traditional rule-based detection can no longer keep pace with adversarial AI. Treating AI like a gardener, not a carpenter One of Cy’s central arguments is that fraud and security teams need to stop micromanaging AI step by step. Instead, let it operate more autonomously. Guided and fed with data, rather than scripted through every decision. This shift, he argues, is essential for AI red team fraud defense to actually outpace attackers moving at machine speed. Fraud and cybersecurity convergence, revisited We return to a theme: why fraud and cybersecurity convergence produces measurably better outcomes. Cy shares how he and Matt Vega built an architecture combining login-state signals with downstream transaction data since the earlier in the funnel an attack is caught, the cheaper it is to stop. Business email compromise isn’t solved We close on a sobering note. BEC remains the FBI’s number one reported fraud category, with billions of dollars in annual losses. Older attack patterns many teams assumed were solved are quietly resurfacing, sharpened by adversarial AI. ### Key takeaways Adversarial AI has moved from theoretical risk to fully operational reality within the past two years. AI phishing attacks can now be generated in minutes using only open source intelligence and a native tool like ChatGPT, no custom infrastructure required. The AI phishing email bypass rate now exceeds 50%, meaning legacy filter-based defenses are no longer sufficient on their own. Fraud and security teams should treat AI as something to nurture and guide, not micromanage step by step. Fraud and cybersecurity convergence, combining login-stage and transaction-stage signals, catches attacks earlier and more cheaply. The real Robinhood phishing attack demonstrates how legitimate infrastructure can be weaponized in ways traditional filters miss entirely. Automated sandboxing fraud detection can analyze and neutralize threats before a user ever interacts with them. Business email compromise remains the FBI's top reported fraud category, and adversarial AI is making it more convincing than ever. Defenders' greatest advantage is collaboration at scale, something adversaries structurally cannot replicate. ### Final takeaway Adversarial AI has already changed the rules. Phishing emails are more convincing, attacks are cheaper to run, and old defenses are failing faster than most teams realize. But the same collaborative instinct that built tools like reCAPTCHA is still the strongest weapon defenders have. The teams that break down the walls between fraud and security, and start sharing data and signals now, will be the ones prepared for what adversarial AI brings next. Episode resources & links Connect with Cy Khormaee | LinkedIn Founder and CEO, Aegis.AI AI Professor, UCLA Connect with Karisse Hendrick | LinkedIn Host of the Fraudology Podcast Award-Winning Cyberfraud Expert Ecommerce Fraud Prevention Consultant Startup Advisor, Keynote Speaker, and Consultant to Fortune 500 merchants