Author

A. Shafran

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#artificial intelligence Preprint Sep 2026

Render Before Reading: Visual Rendering as a Prompt Injection Defense

Large language models are vulnerable to prompt injection attacks, where third-party adversarial content can hijack the model's behavior. In this paper, we study the role played by the adversarial data's input modality, and identify a systematic asymmetry: multimodal LLMs are more likely to follow adversarial instructio...

Jie Zhang, Andrei Baroian, J. V. van Rijn et al. · 0 citations

Jul 2026

CryptanalysisBench: Can LLMs do Cryptanalysis?

This paper introduces CryptanalysisBench, 191 tasks across six families of cryptographic primitives drawn primarily from four NIST standardization competitions, and releases CryptanalysisBench as a tool to help track if (or when) AI cryptanalysis becomes a serious factor and as a scaffold for stress-testing candidate s...

Lukas Fluri, Avital Shafran, Nicholas Carlini et al. · arXiv.org · 1 citation