Mingjie Li, Yukun Jiang, Yicong Tan, Yang Zhang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31152 · open-access PDF
AI 생성 된 이미지가 오늘날 인기를 얻고 있기 때문에 이러한 세대에 대한 토론은 현재 공공 포럼, 소프트웨어 저장소 및 사진 튜토리얼에서 널리 존재합니다.또한 LLM 지원 코드 번역의 도움으로 악성 행위자는 특수 지식이나 결과 도구의 로컬 GPU 실행없이 탐지기를 피하기 위해 그러한 정보를 채택할 수 있습니다.
Machine translation (Meta M2M100); the English original follows.
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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