Image watermarking enables provenance tracing for photorealistic images generated by diffusion models. However, state-of-the-art (SOTA) removal attacks can suppress embedded signals with little perceptual degradation. This vulnerability limits the effectiveness of watermarks for intellectual property protection and mis...
Jie Cao, Qi Li, Chaklam Cheong et al.· 0 citations
Self-evolving LLM coding agents write their own tools by imitating retrieved skills from shared skill libraries. We identify a vulnerability in this loop: during authoring, a retrieved malicious skill can become the template for a new skill that preserves the payload. We call this self-poisoning: the agent authors, sto...
This work introduces RemTraceNet, which fuses constrained residuals, local relations, FFT/Haar statistics, and block-DCT evidence at native resolution and outperforms retrained SRNet, ZhuNet, and SiaStegNet baselines by 10.80--15.68 percentage points.
This work identifies two complementary laundering regimes: OpenAI models produce the strongest payload disruption across the evaluated schemes, whereas Nano Banana 2 shows that DwtDct remains vulnerable under high-fidelity reconstruction.
SkillShield is introduced, a system-prompt defense that synthesizes security skills offline from known attacks or recorded agent failures to prevent harmful actions and malware generation for LLM coding agents.
Xiaodong Wu, Zhimin Zhao, Qi Li et al.· 0 citations
This paper proposes MarkNull, a model-agnostic watermark removal attack via on-manifold latent manipulation that successfully compromise Google's SynthID-Image system while preserving high visual quality and transfer effectively to video watermarking.
Jie Cao, Qi Li, Zelin Zhang et al.· 1 citation
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