Recently I asked a chatbot for a courier's tracking site, and it answered instantly, with total confidence: a clean, plausible-looking address. Helpful, right? Except the bot may have made that address up. And if a scammer registered that exact invented name first, the page that loads looks like the real brand and is built to take your card number. Let's unpack this one together.

Wait, AI makes up website addresses?

Yes, and more often than you'd guess. Large language models (the technology behind chatbots) don't look up facts in a database. They predict text that sounds right. Most of the time that's fine. But when you ask for a specific web address, the model sometimes assembles one that looks completely reasonable, follows the usual pattern for that kind of brand, and simply doesn't belong to anyone. This is called a "hallucination": confident output that isn't true.

With a fact, a hallucination is annoying. With a web address, it's an opening. Because a made-up domain that nobody owns is a domain someone else can go register.

A hallucinated address isn't a typo of the real site. It's a fresh name the model invented, sitting unclaimed, waiting for whoever grabs it first: real brand or scammer.

Phantom squatting: the trick has a name

Security researchers at Unit 42, the threat-intelligence team at Palo Alto Networks, gave this pattern a name in research published on June 30, 2026: phantom squatting. The idea is simple and unsettling. Chatbots repeatedly invent the same plausible brand addresses; attackers register the unclaimed ones and inherit the trust people place in whatever a helpful AI just told them.

To measure it, the team ran 685,339 adversarial prompts across 913 global brands through two families of large language models. Those prompts produced roughly 2.1 million unique web addresses. Among them, 13,229 were already classified as malicious. And the cherry on top: about 250,000 of the invented brand domains were unregistered, sitting available for an attacker to take over.

The Hacker News, reporting on the same study, described the vector bluntly as "inherently unpatchable." There's no software update that stops a model from occasionally inventing a name, and no patch that un-registers a domain a scammer already bought.

How does the trap actually spring?

The most telling part of the research is the timing. Unit 42 found they could predict which hallucinated domains attackers would register 18 to 51 days in advance. In other words, the model invents a name; that name stays quietly available; then, weeks later, a scammer registers it and turns it into a live phishing site.

Their clearest example is a case they call Montana Empire. A hallucinated address for a postal e-commerce marketplace was flagged on March 8, 2026. On March 31, 2026, 23 days later, an attacker registered that exact domain and weaponized it as an AI-built phishing kit designed to steal card details, bank information, and national-ID data.

Realthe brand's actual, registered sitewhat you were looking for
Inventeda plausible address the AI made upunclaimed for weeks, then registered by a scammer

Notice what's different from the classic letter-swap fakes. There's no misspelling to catch, no zero-for-O, no sneaky capital I. The address can look perfectly ordinary, because a brand name plus a normal-looking pattern is exactly what the model produces. The only thing wrong with it is that it was never the real brand's address in the first place. 😅

Where will you run into this?

How do you protect yourself?

The fix isn't to distrust AI entirely. It's to treat any web address a bot hands you as unverified until you've checked it. A few habits:

  1. Don't click a bot's link straight through. Copy the address instead of tapping it, so you can look at it before you go anywhere.
  2. Reach the brand a way you already trust. Type the address you know, use a bookmark, or search for the official site rather than taking the invented one on faith.
  3. Be extra wary of a brand-new-looking domain. A phishing site built on a freshly registered hallucinated name is, by definition, young. A recent registration date on a "known" brand is a red flag.
  4. Paste the address into a checker and see whether it's a known brand's real domain, whether it's been reported, and how old it is, before you type anything into it.

How does IP Tracker help here?

IP Tracker is a free Chrome extension. Paste a domain (or a full email address) into the popup; the free tier gives you 25 checks a day, with no account and no tracking. Only the value you paste is looked up.

For an address a chatbot hands you, it runs several checks at once. It compares the domain against the official domains of roughly 100 widely impersonated brands, so if the invented name is trying to pass as a bank, courier, or payment service you'll see how it lines up. It shows whether Google Safe Browsing (Google's list of reported dangerous sites) has flagged it, how many security vendors flag it on VirusTotal, and any community abuse reports. And it surfaces the domain's creation date, which is the single most useful clue against phantom squatting: a phishing site living on a freshly registered hallucinated domain is often only days old. If the domain is under 90 days old, the banner adds a "Registered N days ago" line as a supporting clue.

What can't it do?

Honesty matters more than comfort here, so a few limits worth knowing:

"Not flagged" is not the same as "safe." Every result is a signal for your judgment, not a verdict. IP Tracker surfaces what it can see about a domain. It can't verify a chatbot's answer for you, and it won't promise a site is safe.

The uncomfortable takeaway from the research is that this vector is, in Unit 42's framing, hard to patch away. Models will keep occasionally inventing plausible names, and the gap between invention and weaponization can be just a few weeks. Your defense isn't technical; it's a pause. When an AI hands you a web address, treat it as a suggestion to verify, not a destination to trust.

To summarize:

Stay sharp, and don't let a confident bot do your checking for you! 😎