arXiv AI June 30, 2026 By Kunyang Li, Kyle Domico, Jonathan Gregory, Patrick McDaniel

MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems

arXiv:2606. 30602v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows.

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

arXiv AI

Jun 16

A Survey on Agentic Security: Applications, Threats and Defenses

arXiv:2510. 06445v3 Announce Type: replace-cross Abstract: LLM-based agents are now used throughout cybersecurity.

By Asif Shahriar, Md Nafiu Rahman, Sadif Ahmed, Farig Sadeque, Md Rizwan Parvez

llms agents safety

arXiv AI

Jul 9

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems

arXiv:2607. 06807v1 Announce Type: cross Abstract: While enabling effective collaboration on complex tasks, LLM-based Multi-Agent Systems (MAS) face critical security challenges due to vulnerabilities at the agent and interaction levels.

By Haowen Xu, Xue Tan, Lei Ma, Zhihao Zhang, Chao Wang, Qingze Wang, Ping Chen, Jun Dai, Xiaoyan Sun

llms agents benchmarks safety

arXiv AI

Jun 15

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

arXiv:2606. 14517v1 Announce Type: cross Abstract: LLM-based guardrails have emerged as a highly effective defense against prompt injection and jailbreak attacks in autonomous agents.

By Yuguang Zhou, Xunguang Wang, Pingchuan Ma, Zhantong Xue, Zhaoyu Wang, Shuai Wang

llms agents benchmarks safety

arXiv AI

1d ago

Beyond Direct Access: Resource Hijacking in LLM Agents

arXiv:2608. 15108v1 Announce Type: cross Abstract: Large language model agents are increasingly connected to high-value resources such as computing infrastructure, credentials, usage budgets, identities, private knowledge, communication channels, and organizational workflows.

By Puyu Zeng, Qibing Ren

llms agents

arXiv AI

Jul 1

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

arXiv:2606. 30755v1 Announce Type: cross Abstract: Claw-like AI agents (e.

By Peizhi Niu, Wenjie Qu, Shangding Gu, Tianneng Shi, Yuankai Li, Ahmad Tawaha, Hend Alzahrani, Vincent Siu, Boyi Li, Chenguang Wang, Jiaheng Zhang, Basel Alomair, Ming Jin, Muhao Chen, Chi Wang, Costas Spanos, Dawn Song

llms agents benchmarks safety

arXiv AI

Jun 10

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation

arXiv:2606. 10749v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly moving from conversational interfaces to software components that plan, invoke tools, maintain memory, and act on external environments.

By Yuchen Ling, Shengcheng Yu, Zhenyu Chen, Chunrong Fang

llms agents benchmarks

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A Survey on Agentic Security: Applications, Threats and Defenses

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems

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

Beyond Direct Access: Resource Hijacking in LLM Agents

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

Toward Secure LLM Agents: Threat Surfaces, Attacks, Defenses, and Evaluation