2,583+ academic papers on AI security, attacks, and defenses
Showing 301–320 of 890 papers
Clear filtersMitchell Piehl, Zhaohan Xi, Zuobin Xiong +2 more
Large language models (LLMs) are increasingly augmented with long-term memory systems to overcome finite context windows and enable persistent...
Xander Davies, Giorgi Giglemiani, Edmund Lau +3 more
Frontier LLMs are safeguarded against attempts to extract harmful information via adversarial prompts known as "jailbreaks". Recently, defenders have...
Lukas Struppek, Adam Gleave, Kellin Pelrine
As the capabilities of large language models continue to advance, so does their potential for misuse. While closed-source models typically rely on...
In Chong Choi, Jiacheng Zhang, Feng Liu +1 more
Multi-turn jailbreak attacks are effective against text-only large language models (LLMs) by gradually introducing malicious content across turns....
Xiaojun Jia, Jie Liao, Simeng Qin +5 more
Agent skills are becoming a core abstraction in coding agents, packaging long-form instructions and auxiliary scripts to extend tool-augmented...
Yuqi Jia, Ruiqi Wang, Xilong Wang +2 more
Prompt injection attacks insert malicious instructions into an LLM's input to steer it toward an attacker-chosen task instead of the intended one....
Ruomeng Ding, Yifei Pang, He Sun +3 more
Evaluation and alignment pipelines for large language models increasingly rely on LLM-based judges, whose behavior is guided by natural-language...
Haoyu Li, Xijia Che, Yanhao Wang +2 more
Proof-of-Vulnerability (PoV) generation is a critical task in software security, serving as a cornerstone for vulnerability validation, false...
Weiming Song, Xuan Xie, Ruiping Yin
Large language models (LLMs) remain vulnerable to jailbreak prompts that elicit harmful or policy-violating outputs, while many existing defenses...
Alfous Tim, Kuniyilh Simi D
The Internet of Things (IoT) systems increasingly depend on continual learning to adapt to non-stationary environments. These environments can...
Osama Zafar, Shaojie Zhan, Tianxi Ji +1 more
In recent years, the widespread adoption of Machine Learning as a Service (MLaaS), particularly in sensitive environments, has raised considerable...
André Storhaug, Jiamou Sun, Jingyue Li
Identifying vulnerability-fixing commits corresponding to disclosed CVEs is essential for secure software maintenance but remains challenging at...
Yannick Assogba, Jacopo Cortellazzi, Javier Abad +3 more
Jailbreak attacks remain a persistent threat to large language model safety. We propose Context-Conditioned Delta Steering (CC-Delta), an SAE-based...
Nate Rahn, Allison Qi, Avery Griffin +3 more
We want language model assistants to conform to a character specification, which asserts how the model should act across diverse user interactions....
Yuepeng Hu, Yuqi Jia, Mengyuan Li +2 more
In a malicious tool attack, an attacker uploads a malicious tool to a distribution platform; once a user installs the tool and the LLM agent selects...
Dong Yan, Jian Liang, Ran He +1 more
Recent studies have shown that large language models (LLMs) can infer private user attributes (e.g., age, location, gender) from user-generated text...
Sri Durga Sai Sowmya Kadali, Evangelos E. Papalexakis
Jailbreaking large language models (LLMs) has emerged as a critical security challenge with the widespread deployment of conversational AI systems....
J Alex Corll
Multi-turn prompt injection attacks distribute malicious intent across multiple conversation turns, exploiting the assumption that each turn is...
Samal Mukhtar, Yinghua Yao, Zhu Sun +3 more
Software vulnerability detection (SVD) is a critical challenge in modern systems. Large language models (LLMs) offer natural-language explanations...
Shuyu Chang, Haiping Huang, Yanjun Zhang +3 more
Code models are increasingly adopted in software development but remain vulnerable to backdoor attacks via poisoned training data. Existing backdoor...
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