2,560+ academic papers on AI security, attacks, and defenses
Showing 201–220 of 727 papers
Clear filtersYong 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...
Amira Guesmi, Muhammad Shafique
Vision-language models (VLMs) have recently shown remarkable capabilities in visual understanding and generation, but remain vulnerable to...
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...
Ruyi Zhang, Heng Gao, Songlei Jian +2 more
Backdoor attacks compromise model reliability by using triggers to manipulate outputs. Trigger inversion can accurately locate these triggers via a...
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...
Md. Abdul Awal, Mrigank Rochan, Chanchal K. Roy
Large language models for code have achieved strong performance across diverse software analytics tasks, yet their real-world adoption remains...
Jianwei Li, Jung-Eun Kim
Backdoor attacks pose severe security threats to large language models (LLMs), where a model behaves normally under benign inputs but produces...
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...
Xiangkui Cao, Jie Zhang, Meina Kan +2 more
Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in...
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...
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,...
Get breaking CVE alerts, compliance reports (ISO 42001, EU AI Act), and CISO risk assessments for your AI/ML stack.
Start 14-Day Free Trial
AI Threat Alert