Flirty OnlyFans promoters on X may be using AI to appear human

In a recent post, we looked at reports of League of Legends players receiving suspicious friend requests shortly after matches. The accounts quickly steered the conversation toward Discord, where they promoted paid adult-content pages.

At the time, one unanswered question was how much of those conversations was automated. Were people working from scripts behind the accounts? Were they conventional, rules-based chatbots following a limited decision tree? Or were they using generative AI to produce more natural and flexible replies?

People are more likely to trust someone they believe is personally interested in them. AI can create that impression across many conversations at once, making it easier to persuade people to click links, spend money, or share personal or intimate information. The same approach could also be used for more harmful fraud, including romance scams and sextortion.

Now, developer Álvaro Martínez Majado has investigated several flirty accounts promoting OnlyFans pages on X to see whether their replies were scripted, generated by AI, or written by people. Majado, president of digital rights organization Protecció de la Frontera Electrònica, shared his evidence with Malwarebytes. Although it does not provide a definitive answer, it shows the accounts following rigid conversation scripts while also responding dynamically to unusual requests. The signs that once suggested a real person, such as an unusual reply or personalized voice note, can no longer be trusted.

The script goes on and on

Majado interacted with several accounts on X that followed a familiar pattern. They opened with similar casual, flirtatious language and asked broadly the same qualifying questions: where he lived, what he liked, and what he did for work.

That repetitive structure is exactly what we would expect from a commercially motivated messaging campaign. The goal is not necessarily to have a meaningful conversation. It is to identify people likely to respond, establish rapport, and eventually move them toward a paid page or another destination controlled by the operator.

The accounts also stayed in character when faced with obvious attempts to expose them as bots. That could be the result of hard-coded replies, guardrails around an AI system, or both.

But some later interactions were more difficult to explain as a simple bank of canned flirtatious responses.

One of the more interesting tests involved an instruction written as ASCII hexadecimal rather than ordinary text. The encoded message told the account to reply with a single word: “Pineapple.”

According to the screenshots supplied to Malwarebytes, the account responded with “Pineapple” in ordinary text.

That does not conclusively prove which technology was used. It does not identify a model, a provider, or the people behind the accounts. But it is consistent with an automated system capable of interpreting an encoded instruction and changing its output accordingly.

A simple scripted bot could theoretically include a hexadecimal decoder, of course. But that would be unusual in a basic adult-content promotional bot, especially when combined with other examples of flexible and sometimes error-prone responses.

In another interaction, Majado asked an account to provide a reply of exactly 12 characters. It responded with “Imnotabotfr”—an 11-character answer—then appeared to recognize its own counting mistake.

Anyone who has spent time experimenting with large language models may recognize the pattern. Language models can be very good at generating natural-sounding text while still making surprisingly basic mistakes involving character counts, word counts, and other exact constraints.

A deliberately designed bot could imitate this kind of mistake, so it is not proof of AI. But the account understood an unexpected instruction, attempted to follow it, and reacted when it got the answer wrong. That suggests it may have been generating replies dynamically rather than choosing from a list of pre-written responses. Such accounts can adapt to conversations, making them harder to identify as automated.

Voice notes do not settle the question

The accounts also sent voice notes. In one example, an account read aloud a Unix timestamp supplied during the conversation. In another, it spoke a requested username.

These responses show that the accounts could incorporate unusual information from a conversation into audio messages. They do not tell us whether a person recorded the clips or a text-to-speech tool generated them.

Text-to-speech tools can generate short, convincing clips quickly and cheaply. An operator can generate them manually, but the process can also be automated: Take a message, pass selected text to a voice-generation service, and send the resulting audio back to the recipient.

Here’s one of those voice notes. Is it a very flirty girl, or AI-generated? Have a listen and see what you think:

The supplied audio metadata offered a possible clue about the tools involved, but it is not enough to attribute the voice notes to a particular service. Platforms and other software can alter audio files and their metadata.

The more important point is that the voice notes were personalized and continued even after the interaction appeared unlikely to lead to a sale. That is consistent with a system designed to keep conversations moving without requiring a human to supervise each one.

AI does not replace the funnel

The evidence does not mean every message from every flirty spam account is written by an AI. Nor does it establish that the X accounts are operated by the same people targeting League of Legends players.

What it does suggest is a plausible hybrid model, supported by identical replies across different accounts alongside more flexible responses.

The repetitive parts of the operation can be scripted: opening messages, questions about location and interests, links, and attempts to move people to another platform. An AI-powered conversational layer could then make the exchange feel less repetitive when someone asks unexpected questions, changes the subject, or tries to test whether the account is real.

This combination makes practical sense for spammers. Scripts provide consistency and keep the conversation directed toward conversion. Generative AI helps the account handle the unpredictable parts of talking to real people.

It also means that traditional “bot tests” are becoming less useful. Asking an account to answer an unusual question, decode a message, or send a

Key Takeaways

• League of Legends players are receiving suspicious friend requests that steer toward Discord promotions.
• Accounts on X promoting OnlyFans may be using AI to appear human when sending friend requests.
• The suspicious friend requests quickly lead to Discord conversations promoting paid adult-content pages.