arXiv AI July 17, 2026 By Jifeng Gao, Kang Xia, Yi Zhang, Xiaobin Hong, Mingkai Lin, Xingshen Wei, Wenzhong Li, Sanglu Lu

MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents

Read the original on arXiv AI →

arXiv:2607. 14651v1 Announce Type: cross Abstract: Persistent external memory enhances agent continuity but introduces persistent security vulnerabilities: adversarial content can be injected via standard interaction channels, retained across turns, and later distort downstream behavior.

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

arXiv AI

Jul 31

MemSecBench: Tracking Agent Memory Poisoning from Persistence to Consequence and Repair

arXiv:2607. 27080v1 Announce Type: cross Abstract: Memory systems allow agents to retain and reuse information from past interactions, but they can also let malicious content persist.

By Xuanze Chen, Xukang Xie, Wentao Fu, Jiajun Zhou, Shanqing Yu, Qi Xuan

llms agents benchmarks

arXiv AI

Jun 4

From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents

arXiv:2606. 04329v1 Announce Type: cross Abstract: Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance.

By Pritam Dash, Tongyu Ge, Aditi Jain, Tanmay Shah, Zhiwei Shang

llms agents benchmarks safety

arXiv AI

Jul 10

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607. 07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks.

By Anupam Wagle, Ifrat Ikhtear Uddin, Chaowei Zhang, Longwei Wang

llms benchmarks safety

arXiv Machine Learning

Jun 10

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

arXiv:2606. 10742v1 Announce Type: cross Abstract: External memory has become a core component of modern web agents, enabling long-horizon reasoning through the retrieval of past experiences.

By Yv Zhang, Hao Sun, Hao Fang, Kuofeng Gao, Fan Mo, Bin Chen, Shu-Tao Xia, Yaowei Wang

llms agents computer-vision multimodal safety

arXiv AI

Aug 5

Injection-Execution Dissociation: A Mechanistic Evaluation of Persistent Memory Attacks and Defenses in Stateful LLM Agents

arXiv:2605. 08442v5 Announce Type: replace-cross Abstract: We discover that prompt-injection success and tool-execution success are separable safety properties: defenses that block injection do not necessarily block execution, and vice versa.

By Jun Wen Leong

llms rag agents benchmarks safety

arXiv AI

Jun 9

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs

arXiv:2606. 07963v1 Announce Type: new Abstract: Backdoor attacks in large language models (LLMs) are often treated as isolated trigger-response failures, motivating defenses tailored to specific triggers or behaviors.

By Omar Mahmoud, Aly M. Kassem, Thommen George Karimpanal, Buddhika Laknath Semage, Negar Rostamzadeh, Golnoosh Farnadi, Santu Rana

llms robotics fine-tuning benchmarks safety

Related stories

MemSecBench: Tracking Agent Memory Poisoning from Persistence to Consequence and Repair

From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

Injection-Execution Dissociation: A Mechanistic Evaluation of Persistent Memory Attacks and Defenses in Stateful LLM Agents

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs