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Raluca A. Popa

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#artificial intelligence Preprint Oct 2026

Pincer: Resource Authorization for Agents using a Digital Twin

Coding agents have become increasingly long-horizon, autonomous, reliant on general-purpose shell and maintain their own persistent memory for self-improvement. While these capabilities have made the agents powerful, they have also made them harder to defend against external adversaries. Defenses that restrict this arc...

Mayank Rathee, Alexander Stepanov, Shalin Madabhavi et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Repeat-After-Me: Black-Box Adaptive Visual Prompt Injection

Prompt injection is widely recognized as a major security threat to AI agents that interact with untrusted external data, such as websites, documents, and emails. Prior work has shown that, in the text domain, black-box prompt injection can achieve near-perfect attack success rates (ASRs). In the image domain, however,...

Si-Zhe Chen, Yu-Lin Tsai, Ivan Evtimov et al. · 1 citation

Hidden Thoughts Are Not Secret: Reasoning Trace Exposure in LLMs

REP, a lightweight in-context elicitation method that uses shadow-model-generated demonstrations wrapped in auxiliary code-like formats to raise user-visible reasoning traces from a victim model, substantially increases similarity between exposed and REP-conditioned internal traces while preserving useful reasoning sig...

Yu-An Lu, Ci-Yang Tsai, Yu-Lin Tsai et al. · 1 citation · ⚡1
Preprint Aug 2026

Daydreaming: Stealing Hidden Agent Skills through Black-Box Task Interaction

Daydreaming is presented, an execution-only attack that steals a multi-file skill through black-box task interactions and produces installable skills using a median of 32 victim calls per skill even with disclosure defenses enabled.

Yu-Lin Tsai, Yu-An Lu, Ci-Yang Tsai et al. · 0 citations

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