arXiv Machine Learning June 9, 2026 By Xinyu Li, Ronghui Mu, Lin Li, Tianjin Huang, Gaojie Jin

OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents

Read the original on arXiv Machine Learning →

arXiv:2605. 08876v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that execute tool-augmented, multi-step tasks, where latency is a critical factor for real-world applications.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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From Shield to Target: Denial-of-Service Attacks on LLM-Based Agent Guardrails

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AdversaBench: Automated LLM Red-Teaming with Multi-Judge Confirmation and Cross-Model Transferability

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