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The Model Context Protocol (MCP) is an emerging standard designed to enable seamless interaction between Large Language Model (LLM) applications and external tools or resources.
Snowball Sampling
Leo A. Goodman · 1961
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Ethereum: A secure decentralised generalised transaction ledger
Gavin Wood et al · 2014
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Quantifying developers’ adoption of security tools
Jim Witschey, Olga Zielinska, Allaire Welk, Emerson Murphy-Hill, Chris Mayhorn, and Thomas Zimmermann · 2015
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An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends
Zibin Zheng, Shaoan Xie, Hongning Dai, Xiangping Chen, and Huaimin Wang · 2017
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Towards Measuring Supply Chain Attacks on Package Managers for Interpreted Languages
Ruian Duan, Omar Alrawi, Ranjita Pai Kasturi, Ryan Elder, Brendan Saltaformaggio, and Wenke Lee · 2021
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Smart Contract Security: A Practitioners’ Perspective
Zhiyuan Wan, Xin Xia, David Lo, Jiachi Chen, Xiapu Luo, and Xiaohu Yang · 2021
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One step further: evaluating interpreters using metamorphic testing
Ming Fan, Jiali Wei, Wuxia Jin, Zhou Xu, Wenying Wei, and Ting Liu · 2022
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Explanation-guided fairness testing through genetic algorithm
Ming Fan, Wenying Wei, Wuxia Jin, Zijiang Yang, and Ting Liu · 2022
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Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz · 2023
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API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Minghao Li, Yingxiu Zhao, Bowen Yu, Feifan Song, Hangyu Li, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li · 2023
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Securing large language models: Threats, vulnerabilities and responsible practices, 2024
Sara Abdali, Richard Anarfi, CJ Barberan, and Jia He · 2024
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A Survey on Evaluation of Large Language Models
Yupeng Chang, Xu Wang, Jindong Wang, et al · 2024
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RMCBench: Benchmarking Large Language Models’ Resistance to Malicious Code
Jiachi Chen, Qingyuan Zhong, Yanlin Wang, Kaiwen Ning, Yongkun Liu, Zenan Xu, Zhe Zhao, Ting Chen, and Zibin Zheng · 2024
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Chatbot arena: An open platform for evaluating LLMs by human preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios N. Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, and Ion Stoica · 2024
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Deepseek-v3 technical report, 2024
DeepSeek-AI · 2024
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The llama 3 herd of models, 2024
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al · 2024
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Prompt injection attack against llm-integrated applications, 2024
Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, Zihao Wang, Xiaofeng Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, and Yang Liu · 2024
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Cheatagent: Attacking llm-empowered recommender systems via llm agent
Liang-bo Ning, Shijie Wang, Wenqi Fan, Qing Li, Xin Xu, Hao Chen, and Feiran Huang · 2024
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GPT-4o, 2024
OpenAI · 2024
Earlier work this paper cites.
Optimization-based prompt injection attack to llm-as-a-judge
Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, and Neil Zhenqiang Gong · 2024
Earlier work this paper cites.
Bdmmt: Backdoor sample detection for language models through model mutation testing
Jiali Wei, Ming Fan, Wenjing Jiao, Wuxia Jin, and Ting Liu · 2024
Earlier work this paper cites.
Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents
Hanrong Zhang, Jingyuan Huang, Kai Mei, Yifei Yao, Zhenting Wang, Chenlu Zhan, Hongwei Wang, and Yongfeng Zhang · 2024
Cited alongside, same era.
Imperceptible content poisoning in llm-powered applications
Quan Zhang, Chijin Zhou, Gwihwan Go, Binqi Zeng, Heyuan Shi, Zichen Xu, and Yu Jiang · 2024
Cited alongside, same era.
Privacyasst: Safeguarding user privacy in tool-using large language model agents
Xinyu Zhang, Huiyu Xu, Zhongjie Ba, Zhibo Wang, Yuan Hong, Jian Liu, Zhan Qin, and Kui Ren · 2024
Cited alongside, same era.
Attacks on Third-Party APIs of Large Language Models
Wanru Zhao, Vidit Khazanchi, Haodi Xing, Xuanli He, Qiongkai Xu, and Nicholas Donald Lane · 2024
Cited alongside, same era.
Claude 3.7 Sonnet, 2025
Anthropic · 2025
Cited alongside, same era.
Claude desktop, 2025
Anthropic · 2025
Gemini 2.5 Pro, 2025
Google · 2025
Closest in time.
Mcp client, how to write system prompt for mcp call tools, 2025
Guolisen · 2025
Closest in time.
Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers, 2025
Mohammed Mehedi Hasan, Hao Li, Emad Fallahzadeh, Gopi Krishnan Rajbahadur, Bram Adams, and Ahmed E. Hassan · 2025
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Model context protocol (mcp): Landscape, security threats, and future research directions, 2025
Xinyi Hou, Yanjie Zhao, Shenao Wang, and Haoyu Wang · 2025
Closest in time.
G-search-mcp, 2025
Jaeger · 2025
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Protocol for system prompts, 2025
Ktalebian · 2025
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Cited alongside, same era.
Get started with the model context protocol (mcp), 2025
Anthropic · 2025
Cited alongside, same era.
Model Context Protocol, 2025
Anthropic · 2025
Cited alongside, same era.
Cursor - the ai code editor, 2025
Anysphere · 2025
Cited alongside, same era.
Base-mcp, 2025
Base · 2025
Cited alongside, same era.
Agent leaderboard, 2025
Pratik Bhavsar · 2025
Cited alongside, same era.
Cline - ai autonomous coding agent for vs code, 2025
Cline Bot · 2025
Cited alongside, same era.
MCP Guardian: A Security-First Layer for Safeguarding MCP-Based AI System, 2025
Sonu Kumar, Anubhav Girdhar, Ritesh Patil, and Divyansh Tripathi · 2025
Closest in time.
A review of prominent paradigms for LLM-based agents: Tool use, planning (including RAG), and feedback learning
Xinzhe Li · 2025
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Datasentinel: A game-theoretic detection of prompt injection attacks, 2025
Yupei Liu, Yuqi Jia, Jinyuan Jia, Dawn Song, and Neil Zhenqiang Gong · 2025
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Playwright-mcp, 2025
Microsoft · 2025
Closest in time.
Enterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies, 2025
Vineeth Sai Narajala and Idan Habler · 2025
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Npx | npm Docs, 2025
Npm · 2025
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Awesome-mcp-servers, 2025
Punkpeye · 2025
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Smithery - Model Context Protocol Registry, 2025
Smithery.ai · 2025
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Cherry studio, 2025
Shanghai Qianhui Technology · 2025
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Using tools | uv, 2025
Uv · 2025
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A comprehensive survey in llm(-agent) full stack safety: Data, training and deployment, 2025
Kun Wang, Guibin Zhang, Zhenhong Zhou, et al · 2025
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Matthew effect, 2025
Wikipedia · 2025
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Benchmarking and defending against indirect prompt injection attacks on large language models
Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, and Fangzhao Wu · 2025
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Defense against prompt injection attacks via mixture of encodings, 2025
Ruiyi Zhang, David Sullivan, Kyle Jackson, Pengtao Xie, and Mei Chen · 2025
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