Adversarial Attacks on AI-Generated Image Detectors

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13 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

WildFakeToolBench: Benchmarking AI-Generated Image Detectors with Web-Sourced Image Processing
Oct 22, 2026Mingjie Li, Yukun Jiang, Yicong Tan +1Adversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection
CISPA Helmholtz Center for Information Security
Tricking Synthetic Image Detectors with Amortized Generative Attacks
Oct 18, 2026Mohamed Awad, Khaled Elhady, Yasser Rohaim +2Adversarial Attacks on AI-Generated Image Detectors Adversarial Attacks
Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi, United Arab Emirates
Can Pixels Alone Reveal Image Origin? Minimax Limits and Learnable Interfaces for Passive Provenance
Sep 25, 2026Kai YaoAdversarial Attacks on AI-Generated Image Detectors Digital Image Forensics
School of Informatics University of Edinburgh
Fusion Under Component Failure: Negative Results and Failure Modes in Ensemble AI-Generated Image Detection
Sep 23, 2026Suraj Singh, Tushar Verma, Pragyan Singh +2Adversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection
Training-Free Reconstruction-Based AI-Generated Image Detectors Are Inherently Vulnerable to Adversarial Examples
Aug 17, 2026Roman Demchenko, Jonas Ricker, Asja FischerAdversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection
Ruhr University Bochum, Bochum, Germany
SPARED: Reasoning-Based AI-Generated Image Detection via Adversarially Edited Data
Aug 13, 2026Yicheng Bao, Xiahui Guo, Xuhong Wang +1Adversarial Training Adversarial Examples
1East China Normal University · 2Shanghai Artificial Intelligence Laboratory
TIGA: Trajectory-Injected Generative Attack against Black-box AIGC Detectors
Jul 28, 2026Xia Du, Zhuosen Bao, Zheng Lin +4Adversarial Attacks Transfer-Based Adversarial Attacks
School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361000, China · Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, L-1855 Luxembourg, Luxembourg · School of Computer Science, Engineering Research Center of Machine Learning and Industry Intelligence, Sichuan University, Chengdu, China, 610020, China +2
Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection
Jul 4, 2026Haoyu Wang, Yiming Qin, Zhongjie Ba +4AI-Generated Image Detection Adversarial Attacks on AI-Generated Image Detectors
State Key Laboratory of Blockchain and Data Security, Zhejiang University · Alibaba Group
TextFake: Benchmarking AI-Generated Image Detection on Text-Rich Images
May 31, 2026Yuning Zhang, Changtao Miao, Mingyu Liao +5AI-Generated Image Detection Adversarial Attacks on AI-Generated Image Detectors
School of Cyber Science and Technology, University of Science and Technology of China · Anhui Province Key Laboratory of Digital Security · Individual Researcher
Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images
Apr 14, 2026Haoyang Jiang, Mingyang Yi, Shaolei Zhang +4Adversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection
Renmin University of China, Beijing, China · Tencent Inc., Shenzhen, China
The Deployment Gap in AI Media Detection: Platform-Aware and Visually Constrained Adversarial Evaluation
Apr 7, 2026Aishwarya Budhkar, Trishita Dhara, Siddhesh ShethAdversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection
Ace Rent a Car
RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image Detectors
Jun 4, 2025Hicham Eddoubi, Jonas Ricker, Federico Cocchi +6Adversarial Robustness AI-Generated Image Detection
University of Cagliari, Italy · Sapienza University of Rome, Italy · Ruhr University Bochum, Germany +3
Adversarial Robustness of AI-Generated Image Detectors in the Real World
Oct 2, 2024Sina Mavali, Jonas Ricker, David Pape +2Adversarial Attacks Adversarial Robustness
CISPA Helmholtz Center for Information Security, Saarbrücken, Germany · Ruhr University Bochum, Bochum, Germany

Oct 22, 2026J/K move · Enter open · S save

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

Mingjie Li, Yukun Jiang, Yicong Tan, Yang Zhang

CISPA Helmholtz Center for Information Security

Adversarial Attacks on AI-Generated Image Detectors AI-Generated Image Detection Black-Box Adversarial Attacks

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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 WildFakeToolBench, a benchmark suite of

156

executable image-processing tools derived from

220

public sources across

142

domains. Each tool retains its source evidence and passes syntax, execution, and output-distortion checks without using feedback from the evaluated detectors. On

105

generated images from five generators, we evaluate six state-of-the-art detectors with images processed by the tools in our collected bench to assess their effectiveness against such in-the-wild risks. The strongest individual tools achieve attack success rates of

25.25\%

100\%

across detectors, exceeding the strongest of six selected image-processing baselines for each detector. Evaluating subsets of an eight-tool pool yields worst-case coverage above

80\%

for every detector. Effectiveness is sparse and detector-specific: high coverage across candidates does not imply reliable one-shot evasion. These findings not only highlight the potential of such web-sourced risks, but also show the potential on establishing AI-image detector robustness evaluation framework based on those in-the-wild information.