Is technology innocent or are tools criminalized? An in-depth analysis of the three main typical patterns of AI agent computing power black and gray industries

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Author: Attorney Shao Shiwei

With the rapid development of AI Agent (artificial intelligence agents) technology, new forms of “black-and-gray” businesses are also beginning to emerge around the business models along its upstream and downstream supply chain.

Within this ecosystem, black-and-gray operators are turning computing power—this core resource that supports AI Agent operations—into an arbitrage object, obtaining it in bulk through technical means and utilizing it in a centralized manner.

These related behaviors are evolving into an arbitrage model featuring organizational, scaled, and technological characteristics. Its basic logic is:

Using common platform growth strategies (such as free trial credits for new users, referral rewards, membership benefits, etc.), obtaining computing power resources through bulk technical means, and then reselling them externally at a lower cost to profit from the price difference.

In the process, these behaviors not only may disrupt platform operations and enforcement mechanisms, and under certain conditions, they may also touch criminal risk.

This article attempts to start from behavior patterns, break down the currently common AI Agent computing power arbitrage routes, and, from a practical perspective, analyze the possible legal risks they may face.

In the AI Agent industry, computing power is essentially a quantifiable cost resource that can be consumed.

Many platforms lower the usage threshold—such as through free trial credits, referral rewards, and similar measures—in order to obtain user scale.

Many people consider registering several additional accounts and using the free trial credits from different platforms; at this stage, most people do not feel there is anything wrong.

But if it gradually becomes not only self-use, but instead begins to obtain these resources in bulk, centrally controlling multiple accounts to run computing power, and even take orders externally, charge fees, or provide services to others for a profit from the price difference, then the nature of the whole matter is no longer the same.

It is precisely through this change that behavior that originally seemed to be merely using platform rules can begin to be understood as an arbitrage approach centered on computing power, and under certain conditions, may fall within the scope of criminal evaluation.

Below, with reference to several typical models, the risks of this kind of behavior will be broken down.

Model 1: Obtain computing power resources by leveraging a platform’s new-user growth mechanism

At present, mainstream platforms typically provide new users with free trial credits to drive user growth, and set up referral reward mechanisms.

Under this mechanism, some people start using automated tools (such as scripts, emulators) to batch-register accounts, repeatedly and in large volumes obtaining the computing power resources provided by the platform, or continuously obtaining referral reward points or computing power by looping through new account registrations and binding invitation codes.

Many people may think this is simply “using the platform’s rules to the extreme,” and there is no big problem. But in actual determinations, the key does not lie in whether those rules are used, but in whether, through technical means, the platform’s verification mechanisms are repeatedly bypassed (such as device recognition, SMS verification, etc.), and whether it forms a method of continuously obtaining resources.

If the behavior has shifted from occasional use to using tools for batch operations and stable resource acquisition, and even further used to provide external services or monetize, then its nature may change.

In some cases, this kind of behavior may be evaluated from the angle of “bypassing systems to obtain platform resources,” involving the crime of illegally obtaining data from a computer information system; if the related behavior relies on special programs or tools used to break through the platform’s protective measures, the manufacture and provision of such tools may also be within the scope of evaluation for the crime of providing programs/tools for intrusion or illegal control of computer information systems; and in scenarios where “fictitious new user” identities are used repeatedly to obtain platform rewards for possession and monetization, there is also risk that it may be analyzed from the perspective of fraud.

Model 2: Use the platform’s high-tier benefits to split and resell computing power

Some platforms offer premium member accounts (such as ChatGPT Plus, team versions), corresponding to higher computing power quotas or permissions for multiple seats. On that basis, some people split a single account’s usage permissions—through “carpooling” or overselling—providing access to multiple downstream users and profiting from the price difference.

Many people will believe this is simply a reuse of purchased rights and benefits, and at most it would constitute a violation of platform user agreements, not something that directly rises to the level of criminal offense. But in actual determinations, it still requires considering the specific source and manner of use.

If it is only sharing or distributing use based on accounts obtained through normal purchase, it generally remains more at the level of breach of contract or unfair competition, and relatively few cases directly escalate to criminal-level situations.

However, if the source of the relevant accounts itself presents problems—for example, obtained at a low price through abnormal means, or associated with the aforementioned bulk acquisition of resources—and then monetized externally through carpooling, resale, and similar methods, then this segment is no longer merely “shared use,” and may instead be evaluated as part of an overall chain of conduct.

In this situation, whether the actor was aware of the account source, whether they participated in subsequent monetization, and whether they profited from it will all become important factors in assessing risk. Under certain circumstances, it may also be analyzed and found liable from perspectives such as the crime of concealing or disguising criminal proceeds.

Model 3: Resale arbitrage by leveraging the platform’s API capabilities

This kind of model can be understood as follows: what the platform provides is a “service capability limited to internal use,” while what black-and-gray operators do is convert that capability into resources that can be sold externally.

By analogy, it is closer to a structure like this: the platform is like a “cafeteria,” allowing users to use services inside the store under the rules (for example, generating content for free on the web interface), but it does not allow these capabilities to be packaged and taken away or offered for interface calls to the outside.

The platform is able to bear these costs based on a premise: most users’ usage is dispersed and limited, so the overall cost is controllable. As for the so-called “API reverse-engineering and parasitic use,” in essence, it adds an additional layer of “pickup and resale” structure outside this system: by obtaining the platform’s internal call paths and verification methods through technical means, converting what was originally fragmented usage into callable abilities that can be centrally scheduled, and then charging external parties for each call in the form of “API services.”

In this process, the platform bears the computing power consumption, while this intermediate layer completes resource consolidation and charges externally. In other words, operations that originally could only be performed within the platform interface are transformed into capabilities that can be batch-called by programs, and then form into an externally charged interface service.

In actual determinations, if the related conduct already involves bypassing the technical measures set up by the platform to restrict access (such as authentication mechanisms, Token verification, etc.) and extracting and reusing the interface logic, it may be analyzed from the perspective of the crime of infringing copyright. If it further provides services externally in forms such as “API forwarding” or “interface services,” and continues to obtain benefits, there is also risk of being evaluated from the perspective of the crime of illegal business operations. And when the relevant request behaviors reach a higher intensity and cause significant impact on the platform’s system operations, or even result in functional disruption, it may also involve the crime of disrupting computer information systems.

Criminal defense lawyer risk warning:

Overall, in the AI Agent field, “computing power arbitrage” behavior has gradually evolved from fragmented operations into multi-tier models that include account acquisition, benefit splitting, and interface resale.

Against the backdrop of the continuous improvement of the digital economy and the rule of law environment, regulation of these emerging cyber “black-and-gray” business practices is tightening. Technology itself has no inherent attributes; the key lies in the manner of use and the real effects it produces.

For practitioners, it is especially important to focus on where their conduct sits within the overall chain, and the nature and risks it thereby presents.

Special statement: This article is an original work by Attorney Shao Shiwei. It only represents the author’s personal views and does not constitute legal consultation or legal advice regarding any specific matter.