2,583+ academic papers on AI security, attacks, and defenses
Showing 121–140 of 658 papers
Clear filtersHanzhi Liu, Chaofan Shou, Hongbo Wen +3 more
Large language model (LLM) agents increasingly rely on third-party API routers to dispatch tool-calling requests across multiple upstream providers....
Yuming Xu, Mingtao Zhang, Zhuohan Ge +5 more
Retrieval-augmented generation (RAG) significantly enhances large language models (LLMs) but introduces novel security risks through external...
Wenpeng Xing, Moran Fang, Guangtai Wang +2 more
While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak attacks that circumvent safety...
Wenkui Yang, Chao Jin, Haisu Zhu +7 more
Existing red-teaming studies on GUI agents have important limitations. Adversarial perturbations typically require white-box access, which is...
Cheng Liu, Xiaolei Liu, Xingyu Li +2 more
Existing jailbreak defense paradigms primarily rely on static detection of prompts, outputs, or internal states, often neglecting the dynamic...
Luat Do, Jiao Yin, Jinli Cao +1 more
Software vulnerabilities continue to pose significant threats to modern information systems, requiring a timely and accurate risk assessment. Public...
Zhiheng Li, Zongyang Ma, Yuntong Pan +8 more
Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a...
Zhiheng Li, Zongyang Ma, Yuntong Pan +8 more
Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a...
Ziye Wang, Guanyu Wang, Kailong Wang
Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs), but simultaneously exposes a critical vulnerability to...
Yizhe Zeng, Wei Zhang, Yunpeng Li +3 more
While Chain-of-Thought (CoT) prompting has become a standard paradigm for eliciting complex reasoning capabilities in Large Language Models, it...
Zi Liang, Qipeng Xie, Jun He +7 more
Recent advancements in Large Language Models (LLMs) have sparked interest in their application to Static Application Security Testing (SAST),...
Phan The Duy, Nguyen Viet Duy, Khoa Ngo-Khanh +2 more
While recent approaches leverage large language models (LLMs) and multi-agent pipelines to automatically generate proof-of-concept (PoC) exploits...
Adrian Shuai Li, Md Ajwad Akil, Elisa Bertino
Concept drift and adversarial evasion are two major challenges for deploying machine learning-based malware detectors. While both have been studied...
Manish Bhatt, Sarthak Munshi, Vineeth Sai Narajala +4 more
We prove that no continuous, utility-preserving wrapper defense-a function $D: X\to X$ that preprocesses inputs before the model sees them-can make...
Zonghao Ying, Haowen Dai, Lianyu Hu +5 more
Modern text-to-image (T2I) models can now render legible, paragraph-length text, enabling a fundamentally new class of misuse. We identify and...
Zonghao Ying, Haowen Dai, Lianyu Hu +5 more
Modern text-to-image (T2I) models can now render legible, paragraph-length text, enabling a fundamentally new class of misuse. We identify and...
Yiyang Zhang, Chaojian Yu, Ziming Hong +4 more
Multimodal pretrained models are vulnerable to backdoor attacks, yet most existing methods rely on visual or multimodal triggers, which are...
Baoshun Tong, Haoran He, Ling Pan +2 more
Vision-Language-Action (VLA) models have achieved remarkable success in robotic manipulation. However, their robustness to linguistic nuances remains...
Yanxu Mao, Peipei Liu, Tiehan Cui +3 more
With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team...
Qingyang Xu, Yaling Shen, Stephanie Fong +7 more
The increasing use of large language models (LLMs) in mental healthcare raises safety concerns in high-stakes therapeutic interactions. A key...
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