Papers

Filtered to encryption · clear filter

Browse by term

continual learning 91reinforcement learning 43vision-language models 18benchmarking 12benchmarks 11robotics 11large language models 10language models 9world models 9video generation 6generative models 5multimodal models 5natural language processing 5recursive self-improvement 5video world models 5agents 4dialogue systems 4diffusion models 4foundation models 4multimodal large language models 4on-policy distillation 4reasoning 4self-distillation 4self-supervised learning 4conversational AI 3evaluation benchmarks 3human-computer interaction 3LLMs 3multi-agent systems 3policy optimization 3

Matching papers

Stealing Reasoning Traces from Proprietary LLM APIs

86 upvotes · 10 AUG 2026 · Alexander Panfilov, David Schmotz, Ilia Shumailov et al.

This paper reveals a vulnerability in how large language model providers store and return their models' step-by-step reasoning, allowing attackers to extract sensitive information and potentially inject malicious code. Practitioners should care because this vulnerability can be exploited to steal proprietary models' reasoning and private data, as well as inject malicious payloads into public models.

large language modelsencryptionvulnerability exploitationdata extractionmodel security