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Documents authored by Kumar, Manish Mahesh

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Emerging Results, Vision & Reflection Track Paper
DOI: 10.4230/LIPIcs.ESEM.2026.57
Emerging Challenges in Threat Modeling for GenAI-Augmented Systems: A View from the Trenches

Authors: Nicolás E. Díaz Ferreyra, Manish Mahesh Kumar, Nohemí Villarreal, Pankaj Pantel, Immo Brueggemann, and Riccardo Scandariato

Published in: LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)

Abstract
Threat modeling remains a central task in secure software engineering, as it enables the identification of security issues from system architectures. As Generative Artificial Intelligence (GenAI) becomes increasingly pervasive across software systems, traditional threat modeling methods (e.g., STRIDE) are insufficient to assess emerging GenAI-specific risks. In this work, we present the first results from an exploratory assessment of GenAI-aware threat modeling methods in a Small and Medium Enterprise (SME) setting. For this, we conducted a rapid literature review to select relevant techniques and systematically applied three shortlisted methods to an industrial case study involving a GenAI-augmented system. The results highlight differences in the threats identified by each technique and reveal limited support for certain GenAI-specific risk categories, particularly those related to software supply chains and human-centered security issues. We further report practitioners' perceptions of the usability and integration of these methods in SME development workflows, including their perceived effort and adoption challenges.
Cite as

Nicolás E. Díaz Ferreyra, Manish Mahesh Kumar, Nohemí Villarreal, Pankaj Pantel, Immo Brueggemann, and Riccardo Scandariato. Emerging Challenges in Threat Modeling for GenAI-Augmented Systems: A View from the Trenches. In 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 394, pp. 57:1-57:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{diazferreyra_et_al:LIPIcs.ESEM.2026.57,
  author =	{D{\'\i}az Ferreyra, Nicol\'{a}s E. and Kumar, Manish Mahesh and Villarreal, Nohem{\'\i} and Pantel, Pankaj and Brueggemann, Immo and Scandariato, Riccardo},
  title =	{{Emerging Challenges in Threat Modeling for GenAI-Augmented Systems: A View from the Trenches}},
  booktitle =	{20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)},
  pages =	{57:1--57:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-450-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{394},
  editor =	{Feldt, Robert and Paasivaara, Maria and Mendez, Daniel and Wagner, Stefan and Bar\'{o}n, Marvin Mu\~{n}oz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.57},
  URN =		{urn:nbn:de:0030-drops-280253},
  doi =		{10.4230/LIPIcs.ESEM.2026.57},
  annote =	{Keywords: Threat Modeling, Software Architectures, Generative AI, ML, Sec4AI}
}

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