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Large Language Models (LLMs) are increasingly deployed in agentic systems that interact with an untrusted environment. However, LLM agents are vulnerable to prompt injection attacks when handling untrusted data. In this paper we propose…

The rapid evolution of Large Language Models (LLMs) into autonomous, tool-calling agents has fundamentally altered the cybersecurity landscape. Frameworks like OpenClaw grant AI systems operating-system-level permissions and the autonomy to…

密码学与安全 · 计算机科学 2026-03-16 Zonghao Ying , Xiao Yang , Siyang Wu , Yumeng Song , Yang Qu , Hainan Li , Tianlin Li , Jiakai Wang , Aishan Liu , Xianglong Liu

Large Language Model (LLM) agents are increasingly proposed to automate offensive security tasks, with recent studies reporting near human-level success rates in Capture-the-Flag (CTF) challenges. We here revisit these results, providing a…

密码学与安全 · 计算机科学 2026-05-22 Youness Bouchari , Matteo Boffa , Marco Mellia , Idilio Drago , Thanh Minh Bui , Dario Rossi

Embodied AI systems, including AI-powered robots that autonomously interact with the physical world, stand to be significantly advanced by Large Language Models (LLMs), which enable robots to better understand complex language commands and…

机器人学 · 计算机科学 2024-09-04 Wenxiao Zhang , Xiangrui Kong , Thomas Braunl , Jin B. Hong

As Large Language Models (LLMs) have made significant advancements across various tasks, such as question answering, translation, text summarization, and dialogue systems, the need for accuracy in information becomes crucial, especially for…

信息检索 · 计算机科学 2024-05-31 Yao Zhao , Zhitian Xie , Chen Liang , Chenyi Zhuang , Jinjie Gu

Large language models (LLMs) have been widely integrated into critical automated workflows, including contract review and job application processes. However, LLMs are susceptible to manipulation by fraudulent information, which can lead to…

密码学与安全 · 计算机科学 2026-02-02 Naen Xu , Jinghuai Zhang , Ping He , Chunyi Zhou , Jun Wang , Zhihui Fu , Tianyu Du , Zhaoxiang Wang , Shouling Ji

Large Language Model-based systems (LLM systems) are information and query processing systems that use LLMs to plan operations from natural-language prompts and feed the output of each successive step into the LLM to plan the next. This…

密码学与安全 · 计算机科学 2024-10-11 Fangzhou Wu , Ethan Cecchetti , Chaowei Xiao

Cybersecurity spans multiple interconnected domains, complicating the development of meaningful, labor-relevant benchmarks. Existing benchmarks assess isolated skills rather than integrated performance. We find that pre-trained knowledge of…

AI safety is a rapidly growing area of research that seeks to prevent the harm and misuse of frontier AI technology, particularly with respect to generative AI (GenAI) tools that are capable of creating realistic and high-quality content…

人工智能 · 计算机科学 2025-02-19 Pin-Yu Chen

Recently, applications powered by Large Language Models (LLMs) have made significant strides in tackling complex tasks. By harnessing the advanced reasoning capabilities and extensive knowledge embedded in LLMs, these applications can…

密码学与安全 · 计算机科学 2025-06-13 Yuyang Zhang , Kangjie Chen , Jiaxin Gao , Ronghao Cui , Run Wang , Lina Wang , Tianwei Zhang

Cybersecurity threats continue to become more sophisticated and diverse in their artifacts, boosting both their volume and complexity. To overcome those challenges, we present GView, an open-source forensic analysis framework with visual…

软件工程 · 计算机科学 2025-09-17 Raul Zaharia , Dragoş Gavriluţ , Gheorghiţă Mutu

To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, Frontier AI Risk Management Framework in Practice presents a comprehensive assessment of their frontier risks. As Large…

Large Language Models (LLMs) have significantly advanced natural language processing (NLP), providing versatile capabilities across various applications. However, their application to complex, domain-specific tasks, such as cyber-security,…

计算与语言 · 计算机科学 2024-08-20 Matan Levi , Yair Alluouche , Daniel Ohayon , Anton Puzanov

Ensuring the security of critical infrastructure has become increasingly vital with the proliferation of Internet of Things (IoT) systems. However, the heterogeneous nature of IoT data and the lack of human-comprehensible insights from…

密码学与安全 · 计算机科学 2025-10-07 Ashutosh Ghimire , Ghazal Ghajari , Karma Gurung , Love K. Sah , Fathi Amsaad

Over the last year, significant advancements have been made in the realms of large language models (LLMs) and multi-modal large language models (MLLMs), particularly in their application to autonomous driving. These models have showcased…

机器人学 · 计算机科学 2024-06-11 Xiangrui Kong , Thomas Braunl , Marco Fahmi , Yue Wang

As AI systems increasingly influence critical decisions, they face threats that exploit reasoning mechanisms rather than technical infrastructure. We present a framework for cognitive cybersecurity, a systematic protection of AI reasoning…

密码学与安全 · 计算机科学 2025-08-25 Yuksel Aydin

Large Language Models (LLMs) continue to exhibit vulnerabilities to jailbreaking attacks: carefully crafted malicious inputs intended to circumvent safety guardrails and elicit harmful responses. As such, we present AutoAdv, a novel…

密码学与安全 · 计算机科学 2025-12-25 Aashray Reddy , Andrew Zagula , Nicholas Saban

In an era where digital threats are increasingly sophisticated, the intersection of Artificial Intelligence and cybersecurity presents both promising defenses and potent dangers. This paper delves into the escalating threat posed by the…

密码学与安全 · 计算机科学 2024-08-26 Yusuf Usman , Aadesh Upadhyay , Prashnna Gyawali , Robin Chataut

Protecting cloud applications is critical in an era where security threats are increasingly sophisticated and persistent. Continuous Integration and Continuous Deployment (CI/CD) pipelines are particularly vulnerable, making innovative…

密码学与安全 · 计算机科学 2025-10-21 Sabbir M. Saleh , Nazim Madhavji , John Steinbacher

Large language models (LLMs) have shown remarkable capabilities in various natural language tasks and are increasingly being applied in healthcare domains. This work demonstrates a new LLM-powered disease risk assessment approach via…

计算与语言 · 计算机科学 2024-09-24 Mohammad Amin Roshani , Xiangyu Zhou , Yao Qiang , Srinivasan Suresh , Steve Hicks , Usha Sethuraman , Dongxiao Zhu