Impersonation tactics, such as app squatting and app cloning, have posed longstanding challenges in the mobile app industry, where malicious actors exploit the names and reputations of popular apps to deceive users. With the rapid growth of large language model (LLM) stores like GPT Store and FlowGPT, these issues have similarly surfaced, highlighting the urgent need for robust industry standards and automated detection mechanisms to safeguard the LLM app ecosystem and protect users from fraudulent practices. In this study, we present the first large-scale analysis of LLM app squatting and cloning using our custom-built tool, LLMappCrazy. LLMappCrazy covers 14 squatting generation techniques and integrates Levenshtein distance and BERT-based semantic analysis to detect cloning by analyzing app functional similarities. Using this tool, we generated variations of the top 1000 app names and found over 5,000 squatting LLM apps in the dataset. Additionally, we observed 13,325 cloning cases across six major platforms. After sampling, we find that 4.7% of the squatting apps and 18.4% of the cloning apps exhibited malicious behavior, including phishing, malware distribution, fake content dissemination, and aggressive ad injection. Our work provides actionable insights for industry stakeholders to address these growing threats and foster a safer, more trustworthy LLM app ecosystem.
Wed 25 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:30 | LLM and PromptIndustry Papers / Ideas, Visions and Reflections / Research Papers / Journal First at Cosmos 3B Chair(s): Giuseppe Scanniello University of Salerno | ||
11:00 20mTalk | On Inter-dataset Code Duplication and Data Leakage in Large Language Models Journal First José Antonio Hernández López Linköping University, Boqi Chen McGill University, Mootez Saad Dalhousie University, Tushar Sharma Dalhousie University, Daniel Varro Linköping University / McGill University | ||
11:20 20mTalk | LLM App Squatting and Cloning Industry Papers Yinglin Xie Huazhong University of Science and Technology, Xinyi Hou Huazhong University of Science and Technology, Yanjie Zhao Huazhong University of Science and Technology, Kai Chen Huazhong University of Science and Technology, Haoyu Wang Huazhong University of Science and Technology | ||
11:40 10mTalk | Predictive Prompt Analysis Ideas, Visions and Reflections | ||
11:50 20mTalk | From Prompts to Templates: A Systematic Prompt Template Analysis for Real-world LLMapps Industry Papers Yuetian Mao Technical University of Munich, Junjie He Technical University of Munich, Chunyang Chen TU Munich | ||
12:10 20mTalk | Prompts Are Programs Too! Understanding How Developers Build Software Containing Prompts Research Papers Jenny T. Liang Carnegie Mellon University, Melissa Lin Carnegie Mellon University, Nikitha Rao Carnegie Mellon University, Brad A. Myers Carnegie Mellon University DOI | ||
Cosmos 3B is the second room in the Cosmos 3 wing.
When facing the main Cosmos Hall, access to the Cosmos 3 wing is on the left, close to the stairs. The area is accessed through a large door with the number “3”, which will stay open during the event.