2,077+ academic papers on AI security, attacks, and defenses
Showing 281–300 of 715 papers
Clear filtersJonah Ghebremichael, Saastha Vasan, Saad Ullah +6 more
Static Application Security Testing (SAST) tools using taint analysis are widely viewed as providing higher-quality vulnerability detection results...
Hao Wang, Yanting Wang, Hao Li +2 more
Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to adversarial ``jailbreak'' attacks designed to bypass...
Yinzhi Zhao, Ming Wang, Shi Feng +3 more
Large language models (LLMs) have achieved impressive performance across natural language tasks and are increasingly deployed in real-world...
Yuansen Liu, Yixuan Tang, Anthony Kum Hoe Tun
Current LLM safety research predominantly focuses on mitigating Goal Hijacking, preventing attackers from redirecting a model's high-level objective...
Hao Li, Yankai Yang, G. Edward Suh +2 more
Large Language Models (LLMs) have enabled the development of powerful agentic systems capable of automating complex workflows across various fields....
Oleg Brodt, Elad Feldman, Bruce Schneier +1 more
Prompt injection was initially framed as the large language model (LLM) analogue of SQL injection. However, over the past three years, attacks...
Zhiyi Mou, Jingyuan Yang, Zeheng Qian +6 more
While Large Language Models (LLMs) have powerful capabilities, they remain vulnerable to jailbreak attacks, which is a critical barrier to their safe...
Xiaonan Liu, Zhihao Li, Xiao Lan +3 more
Capture-the-Flag (CTF) competitions play a central role in modern cybersecurity as a platform for training practitioners and evaluating offensive and...
Fengchao Chen, Tingmin Wu, Van Nguyen +1 more
Large Language Models (LLMs) have enabled agents to move beyond conversation toward end-to-end task execution and become more helpful. However, this...
Shaznin Sultana, Sadia Afreen, Nasir U. Eisty
Context: Traditional software security analysis methods struggle to keep pace with the scale and complexity of modern codebases, requiring...
Mohammed Himayath Ali, Mohammed Aqib Abdullah, Mohammed Mudassir Uddin +1 more
Large Language Models have emerged as transformative tools for Security Operations Centers, enabling automated log analysis, phishing triage, and...
Xinyi Wu, Geng Hong, Yueyue Chen +5 more
Web agents, powered by large language models (LLMs), are increasingly deployed to automate complex web interactions. The rise of open-source...
Shawn Li, Chenxiao Yu, Zhiyu Ni +4 more
Large language models (LLMs) are increasingly deployed in security-sensitive applications, where they must follow system- or developer-specified...
Hongyan Chang, Ergute Bao, Xinjian Luo +1 more
Large language models (LLMs) increasingly rely on retrieving information from external corpora. This creates a new attack surface: indirect prompt...
Harshil Parmar, Pushti Vyas, Prayers Khristi +1 more
As vulnerability research increasingly adopts generative AI, a critical reliance on opaque model outputs has emerged, creating a "trust gap" in...
Masahiro Kaneko
The use of large language models (LLMs) in peer review systems has attracted growing attention, making it essential to examine their potential...
Muhammad Wahid Akram, Keshav Sood, Muneeb Ul Hassan +1 more
Phishing with Quick Response (QR) codes is termed as Quishing. The attackers exploit this method to manipulate individuals into revealing their...
Quan Minh Nguyen, Min-Seon Kim, Hoang M. Ngo +3 more
Membership inference attack (MIA) poses a significant privacy threat in federated learning (FL) as it allows adversaries to determine whether a...
Hongjun An, Yiliang Song, Jiangan Chen +3 more
Large Language Model (LLM) training often optimizes for preference alignment, rewarding outputs that are perceived as helpful and...
Víctor Mayoral-Vilches, María Sanz-Gómez, Francesco Balassone +6 more
AI-driven penetration testing now executes thousands of actions per hour but still lacks the strategic intuition humans apply in competitive...
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