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Paper Abstract and Keywords
Presentation 2026-06-17 11:25
An Empirical Evaluation of AI Agents for Detecting and Fixing Software Vulnerabilities
Yuya Noguchi, Yo Kanemoto (former NTT) IA2026-5 ICSS2026-5
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, research on automated vulnerability repair using AI agents based on large language models has become increasingly active. Multi-agent configurations have been proposed in which the roles of vulnerability detection, vulnerability repair, and patch evaluation are assigned to separate agents. However, the extent to which such configurations affect vulnerability repair performance has not been sufficiently organized or empirically examined. In this study, we compare a multi-agent configuration consisting of vulnerability detection, vulnerability repair, and patch evaluation roles with a single-agent configuration. We also conduct an ablation study for each role to investigate how differences in agent configuration affect vulnerability repair tasks. The purpose of this study is to clarify the effectiveness and challenges of role separation in AI-agent-based vulnerability repair and to provide insights for the research community.
Keyword (in Japanese) (See Japanese page) 
(in English) AI Agent / Automated Vulnerability Repair / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 74, ICSS2026-5, pp. 24-29, June 2026.
Paper # ICSS2026-5 
Date of Issue 2026-06-10 (IA, 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 IA2026-5 ICSS2026-5

Conference Information
Committee IA ICSS  
Conference Date 2026-06-17 - 2026-06-18 
Place (in Japanese) (See Japanese page) 
Place (in English) e-Topia, Kagawa BB Square 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Internet Security, etc. 
Paper Information
Registration To ICSS 
Conference Code 2026-06-IA-ICSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Empirical Evaluation of AI Agents for Detecting and Fixing Software Vulnerabilities 
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Keyword(1) AI Agent  
Keyword(2) Automated Vulnerability Repair  
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1st Author's Name Yuya Noguchi  
1st Author's Affiliation NTT Social Informatics Laboratories (former NTT)
2nd Author's Name Yo Kanemoto  
2nd Author's Affiliation NTT Social Informatics Laboratories (former NTT)
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Speaker Author-1 
Date Time 2026-06-17 11:25:00 
Presentation Time 25 minutes 
Registration for ICSS 
Paper # IA2026-5, ICSS2026-5 
Volume (vol) vol.126 
Number (no) no.73(IA), no.74(ICSS) 
Page pp.24-29 
#Pages 6 
Date of Issue 2026-06-10 (IA, ICSS) 

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