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Paper Abstract and Keywords
Presentation 2025-03-06 13:45
Large-Scale Analysis of Malicious Packages on PyPI Using LLM Agents
Takaaki Toda (Waseda University/RIKEN AIP), Takuro Wakai (Waseda University), Tatsuya Mori (Waseda University/NICT/RIKEN AIP) ICSS2024-80
Abstract (in Japanese) (See Japanese page) 
(in English) Package registries enable software developers to easily reuse source code and are essential for modern software development. However, their widespread use has led to the distribution of malicious packages containing malware. Addressing these threats requires a systematic analysis of higher-level contextual information, such as the deployment methods and intent of malicious code.
This study explores an automated, context-aware analysis of malicious packages on PyPI, the Python package registry. Previous research relied on rule-based methods, which struggle to capture contextual information. To overcome this, we implemented an LLM agent to enhance and automate malicious package analysis.
To evaluate our approach, we conducted a large-scale study using about 9,000 samples from an existing dataset. Our results identified common characteristics of malicious packages on PyPI and demonstrated the effectiveness of LLM-based analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) Package Registries / PyPI / Supply Chain Risk / LLM Agent / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 422, ICSS2024-80, pp. 84-91, March 2025.
Paper # ICSS2024-80 
Date of Issue 2025-02-27 (ICSS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF ICSS2024-80

Conference Information
Committee ICSS IPSJ-SPT  
Conference Date 2025-03-06 - 2025-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Prefectural Museum & Art Museum 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Security, Trust, etc. 
Paper Information
Registration To ICSS 
Conference Code 2025-03-ICSS-SPT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Large-Scale Analysis of Malicious Packages on PyPI Using LLM Agents 
Sub Title (in English)  
Keyword(1) Package Registries  
Keyword(2) PyPI  
Keyword(3) Supply Chain Risk  
Keyword(4) LLM Agent  
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Keyword(6)  
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Keyword(8)  
1st Author's Name Takaaki Toda  
1st Author's Affiliation Waseda University/RIKEN AIP (Waseda University/RIKEN AIP)
2nd Author's Name Takuro Wakai  
2nd Author's Affiliation Waseda University (Waseda University)
3rd Author's Name Tatsuya Mori  
3rd Author's Affiliation Waseda University/National Institute of Information and Communications Technology/RIKEN AIP (Waseda University/NICT/RIKEN AIP)
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Speaker Author-1 
Date Time 2025-03-06 13:45:00 
Presentation Time 20 minutes 
Registration for ICSS 
Paper # ICSS2024-80 
Volume (vol) vol.124 
Number (no) no.422 
Page pp.84-91 
#Pages 8 
Date of Issue 2025-02-27 (ICSS) 

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