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20162025
most citedStealing Machine Learning Models via Prediction APIs

733 citations · 902 across the 19 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.LG20253 cited

The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections

Milad Nasr, Nicholas Carlini, Chawin Sitawarin +11

How should we evaluate the robustness of language model defenses? Current defenses against jailbreaks and prompt injections (which aim to prevent an attacker from eliciting harmful…

cs.LG20253 cited

Design Patterns for Securing LLM Agents against Prompt Injections

Luca Beurer-Kellner, Beat Buesser, Ana-Maria Creţu +11

As AI agents powered by Large Language Models (LLMs) become increasingly versatile and capable of addressing a broad spectrum of tasks, ensuring their security has become a critica…

cs.CR2025

Membership Inference Attacks on Sequence Models

Lorenzo Rossi, Michael Aerni, Jie Zhang +1

Sequence models, such as Large Language Models (LLMs) and autoregressive image generators, have a tendency to memorize and inadvertently leak sensitive information. While this tend…

cs.LG2025

Pitfalls in Evaluating Language Model Forecasters

Daniel Paleka, Shashwat Goel, Jonas Geiping +1

Large language models (LLMs) have recently been applied to forecasting tasks, with some works claiming these systems match or exceed human performance. In this paper, we argue that…

cs.CR2025

LLMs unlock new paths to monetizing exploits

Nicholas Carlini, Milad Nasr, Edoardo Debenedetti +5

We argue that Large language models (LLMs) will soon alter the economics of cyberattacks. Instead of attacking the most commonly used software and monetizing exploits by targeting…

cs.LG2025

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?

Kristina Nikolić, Luze Sun, Jie Zhang +1

Jailbreak attacks bypass the guardrails of large language models to produce harmful outputs. In this paper, we ask whether the model outputs produced by existing jailbreaks are act…