[2603.01919] Real Money, Fake Models: Deceptive Model Claims in Shadow APIs

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arXiv:2603.01919 (cs)

[Submitted on 2 Mar 2026 (v1), last revised 5 Mar 2026 (this version, v2)]

Title:Real Money, Fake Models: Deceptive Model Claims in Shadow APIs

Authors:Yage Zhang, Yukun Jiang, Zeyuan Chen, Michael Backes, Xinyue Shen, Yang Zhang<br>View a PDF of the paper titled Real Money, Fake Models: Deceptive Model Claims in Shadow APIs, by Yage Zhang and 5 other authors

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Abstract:Access to frontier large language models (LLMs), such as GPT-5 and Gemini-2.5, is often hindered by high pricing, payment barriers, and regional restrictions. These limitations drive the proliferation of $\textit{shadow APIs}$, third-party services that claim to provide access to official model services without regional limitations via indirect access. Despite their widespread use, it remains unclear whether shadow APIs deliver outputs consistent with those of the official APIs, raising concerns about the reliability of downstream applications and the validity of research findings that depend on them. In this paper, we present the first systematic audit between official LLM APIs and corresponding shadow APIs. We first identify 17 shadow APIs that have been utilized in 187 academic papers, with the most popular one reaching 5,966 citations and 58,639 GitHub stars by December 6, 2025. Through multidimensional auditing of three representative shadow APIs across utility, safety, and model verification, we uncover both indirect and direct evidence of deception practices in shadow APIs. Specifically, we reveal performance divergence reaching up to $47.21\%$, significant unpredictability in safety behaviors, and identity verification failures in $45.83\%$ of fingerprint tests. These deceptive practices critically undermine the reproducibility and validity of scientific research, harm the interests of shadow API users, and damage the reputation of official model providers.

Subjects:

Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Software Engineering (cs.SE)

Cite as:<br>arXiv:2603.01919 [cs.CR]

(or<br>arXiv:2603.01919v2 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2603.01919

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arXiv-issued DOI via DataCite

Submission history<br>From: Yukun Jiang [view email]<br>[v1]<br>Mon, 2 Mar 2026 14:33:05 UTC (9,168 KB)

[v2]<br>Thu, 5 Mar 2026 00:42:02 UTC (9,386 KB)

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