Forging Tree-Ring: Reproducing and Instrumenting Black-Box Semantic Watermark Forgery
Reprompt watermark forgery reproduces on Stable Diffusion XL using free-tier T4 GPUs, with forged images accepted by the genuine detector 5 of 6 times.
The authors reproduce the Reprompt forgery attack of Müller et al. against Tree-Ring watermarking on Stable Diffusion XL using the released code on free-tier dual T4 GPUs with 14.6 GB usable memory, versus the A40 hardware of the original study. Over six trials, the genuine detector flagged genuine images 6/6, clean images 0/6, and forged images 5/6, at 325-332 seconds per attack. They also recovered the detector's discarded non-central chi-square statistic and built two natural scores separating forged images from the clean null at AUC 0.861 and 0.972. The notebook, pinned fork, and all measurement artifacts are released with the paper.
- Reprompt forgery reproduced on SDXL with free-tier dual T4 GPUs (14.6 GB).
- Genuine detector accepts forged images in 5 of 6 trials.
- Recovered chi-square statistic separates forged from clean at AUC 0.972.
- Attack runs at 325-332 seconds per image on constrained hardware.
- Notebook, pinned fork, and measurement artifacts publicly released.
Full article237 words · extracted from arxiv.org · click to collapse
Semantic watermarking schemes such as Tree-Ring hide a detectable pattern in the initial noise latent of a diffusion model. Recent work shows these watermarks are not only removable but forgeable: an attacker who never sees the watermarking key can still produce images the genuine detector accepts. We reproduce the Reprompt forgery attack of Müller et al. against Tree-Ring on Stable Diffusion XL, using the authors' released code, on free-tier dual T4 GPUs with 14.6 GB of usable memory per device, substantially less per-GPU memory than the A40 hardware used in the original study. The attack reproduces. Over six trials of three arms we detect genuine images 6/6, clean images 0/6, and forged images 5/6, at 325-332 s per attack. Three further results came out of running it under constraint. The released detector computes a non-central $χ^2$ statistic and hands back only its CDF, so we recovered the discarded statistic; our recovery matches the released detector exactly, and two natural scores built from it separate the forged arm from the clean null at AUC 0.861 and 0.972 on the same eighteen observations. Running SDXL in half precision requires patching the pipeline's direct autoencoder calls, and a controlled probe confirms the patched path leaves the detector statistic unchanged. Finally, we report a prediction we made from reading the detector source that our measurements then contradicted. The notebook, the pinned fork and every measurement artifact are released with the paper.
Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.12909