2,077+ academic papers on AI security, attacks, and defenses
Showing 21–40 of 102 papers
Clear filtersShenao Yan, Shimaa Ahmed, Shan Jin +4 more
Code generation large language models (LLMs) are increasingly integrated into modern software development workflows. Recent work has shown that these...
Yong Zou, Haoran Li, Fanxiao Li +5 more
Recent progress in image generation models (IGMs) enables high-fidelity content creation but also amplifies risks, including the reproduction of...
Guangsheng Zhang, Huan Tian, Leo Zhang +4 more
Semantic segmentation models are widely deployed in safety-critical applications such as autonomous driving, yet their vulnerability to backdoor...
Deng Liu, Song Chen
Hardware faults, specifically bit-flips in quantized weights, pose a severe reliability threat to Large Language Models (LLMs), often triggering...
Xiaobing Sun, Perry Lam, Shaohua Li +4 more
Modern LLMs employ safety mechanisms that extend beyond surface-level input filtering to latent semantic representations and generation-time...
Yihao Zhang, Zeming Wei, Xiaokun Luan +7 more
Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security...
Yihao Zhang, Zeming Wei, Xiaokun Luan +7 more
Autonomous LLM-based agents increasingly operate as long-running processes forming densely interconnected multi-agent ecosystems, whose security...
Mateusz Dziemian, Maxwell Lin, Xiaohan Fu +28 more
LLM based agents are increasingly deployed in high stakes settings where they process external data sources such as emails, documents, and code...
Zhenlin Xu, Xiaogang Zhu, Yu Yao +2 more
Modern agentic systems allow Large Language Model (LLM) agents to tackle complex tasks through extensive tool usage, forming structured control flows...
Lidor Erez, Omer Hofman, Tamir Nizri +1 more
Automated LLM vulnerability scanners are increasingly used to assess security risks by measuring different attack type success rates (ASR). Yet the...
Maël Jenny, Jérémie Dentan, Sonia Vanier +1 more
Most jailbreak techniques for Large Language Models (LLMs) primarily rely on prompt modifications, including paraphrasing, obfuscation, or...
Chongxin Li, Hanzhang Wang, Lian Duan
Safety prompts constitute an interpretable layer of defense against jailbreak attacks in vision-language models (VLMs); however, their efficacy is...
Yiling Tao, Xinran Zheng, Shuo Yang +2 more
While large language model-based agents demonstrate great potential in collaborative tasks, their interactivity also introduces security...
Zijian Ling, Pingyi Hu, Xiuyong Gao +6 more
Speech-driven large language models (LLMs) are increasingly accessed through speech interfaces, introducing new security risks via open acoustic...
Chenlong Yin, Runpeng Geng, Yanting Wang +1 more
Prompt injection poses serious security risks to real-world LLM applications, particularly autonomous agents. Although many defenses have been...
Zheng Gao, Yifan Yang, Xiaoyu Li +4 more
Watermarking the initial noise of diffusion models has emerged as a promising approach for image provenance, but content-independent noise patterns...
Sihao Ding
We introduce Colluding LoRA (CoLoRA), an attack in which each adapter appears benign and plausibly functional in isolation, yet their linear...
Darren Cheng, Wen-Kwang Tsao
Prompt injection remains one of the most practical attack vectors against LLM-integrated applications. We replicate the Microsoft LLMail-Inject...
Siddharth Srikanth, Freddie Liang, Sophie Hsu +9 more
Vision-Language-Action (VLA) models have significant potential to enable general-purpose robotic systems for a range of vision-language tasks....
Xinhai Wang, Shaopeng Fu, Shu Yang +3 more
Suffix jailbreak attacks serve as a systematic method for red-teaming Large Language Models (LLMs) but suffer from prohibitive computational costs,...
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