In July 2025, researchers reported that hackers were abusing Vercel’s new AI website creation tool “v0” to spin up phishing sites in under thirty seconds. The tool, designed to help developers prototype quickly, was used to generate convincing clones of login portals for companies like Okta, Google, and Microsoft.
By impersonating trusted brands with highly accurate spoofs, attackers exploit the confidence users place in familiar logos and interfaces, making it easier to trick them into handing over credentials, payment data, or other sensitive information. Once this information falls into the hands of criminal groups, they can use it to infiltrate companies, drain financial accounts, or resell their access on dark web markets.
This is the new face of impersonation. AI is fueling large-scale digital brand impersonation across websites, login portals, and search engines. Attacker infrastructure that once took weeks to develop is now accessible at scale with the help of commodity AI tools.
Why AI Impersonation is Exploding
AI impersonation is thriving because the barrier to entry has collapsed. Generative AI tools make it trivial to clone brand assets, spin up fake domains, and launch phishing sites in minutes.
Another driver is the growing attack surface. Remote work, digital banking, and reliance on cloud applications mean that customers interact with brands primarily through web portals, video calls, and mobile apps. All of these channels can be spoofed with AI.
Add to that the abundance of public data available for the most popular brands, and you have the perfect recipe for a thriving brand impersonation ecosystem.
The ecosystem is fueled by a well-organized dark web economy where criminal groups trade phishing kits, AI-generated site templates, stolen credentials, and even “impersonation-as-a-service” packages. Unskilled criminals now have access to the same capabilities that once took real expertise and significant time to develop.
How These Scams Work
AI digital impersonation starts with attackers scraping public information about the brand they want to mimic. Nowadays, even this process can be automated. The AI can find all relevant logos, copy, UI patterns, and executive voices, then use them to generate near-perfect phishing sites. The most common impersonation assets are login pages, with payment and checkout forms not too far behind.
Once ready, the spoofed assets launch fast using fake domains and SSL certificates. Attackers may even hijack real, forgotten subdomains through subdomain takeover, which allows them to host convincing brand clones on seemingly legitimate addresses.
To spread, attackers typically use paid ads to rank high in search engines or send phishing emails to trick users into accessing the fake pages. For example, an employee might get an urgent request to reset their password on a vendor portal, which is in fact a cloned password-reset page designed to steal credentials.
Since phishing emails remain the primary delivery channel for these scams, stopping them at the inbox is critical. Leading email security vendors like Proofpoint are expanding their AI-driven capabilities to catch even the most subtle signals in phishing attempts.
By analyzing details that humans can’t check in real time, such as unusual domain registrations or abnormal sender behavior, Proofpoint quickly determines the legitimacy of messages before they land in an employee’s inbox.
Why Humans Alone Can’t Spot AI Impersonation
The challenge with AI-driven impersonation is that it no longer looks fake. Until recently, even the best spoofed sites had little inconsistencies that gave them away. Now, everything looks almost perfect.
The same can be said about emails, voice calls, and even live video. Generative AI generates emails in perfect English that match the tone of corporate comms, while deepfake technology replicates facial expressions and voice patterns so convincingly that fake meetings or urgent calls feel entirely real.
Another problem is the overconfidence that most people have in their ability to spot phishing attempts. Recent research from KnowBe4 shows that while 86% of employees believe they can confidently identify phishing emails, nearly half have fallen for scams in practice.
Relying on human intuition is no longer enough. To combat AI-powered impersonation, organizations need a combination of quality employee awareness training and automated defenses to detect, block, and disrupt scams the moment they appear.
Defenses That Work Heading into 2026
The best way to combat AI impersonation is with multiple layers of defense.
At the human layer, regular security awareness training remains essential. Employees need realistic and relevant simulations that mirror the latest AI-driven phishing and impersonation tactics so they can recognize and respond before damage is done.
On the technology front, organizations can combine strong email and gateway defenses to prevent phishing lures before they reach users with real-time brand protection to spot and neutralize fake sites as they appear.
For example, preemptive cybersecurity firm Memcyco uses an agentless approach to detect spoofed assets in real time. When attackers attempt to harvest credentials, its platform replaces stolen data with marked decoy information. Because the attacker only ever receives decoys, the breach is contained immediately.
But on top of that, the marked data acts as a tracking signal, much like marked money from a bank, exposing attacker infrastructure and bringing valuable intelligence to defenders.
The key is to layer defenses so that if one control fails, another is ready to take over. Even a well-trained employee can fall for phishing and give out their credentials, but the brand protection service will step in and contain the threat.
Conclusion
AI impersonation scams took off in 2025 and will likely remain one of the top risks companies face as AI continues to evolve (for better or worse) in 2026.
Investing in a proactive and layered detection strategy is the only way to handle the scale and sophistication of modern impersonation attacks. Organizations that treat impersonation as a true operational risk will be the ones that survive the next wave.
