WildFakeToolBench: Benchmarking AI-Generated Image Detectors with Web-Sourced Image Processing

Mingjie Li, Yukun Jiang, Yicong Tan, Yang Zhang · 2026 · arXiv

DOI: 10.48550/arXiv.2610.31152 · open-access PDF

Abstract

As AI generated images are getting popular these days, discussions on such generations are widely existed in current public forums, software repositories, and photography tutorials. Moreover, with the help of LLM-assisted code translation, malicious actors can adopt such information to evade detectors without specialized knowledge or local GPU execution of the resulting tools. To evaluate such risks, we introduce \textsc{WildFakeToolBench}, a benchmark suite of $156$ executable image-processing tools derived from $220$ public sources across $142$ domains. Each tool retains its source evidence

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