SEMar 24

Towards Leveraging LLMs to Generate Abstract Penetration Test Cases from Software Architecture

arXiv:2603.2369821.3h-index: 4
AI Analysis

This addresses security vulnerabilities early in software development for architects and penetration testers, though it is incremental as it applies existing LLMs to a new domain.

The paper tackles the problem of missing security assessment at the software architecture stage by generating Abstract Penetration Test Cases (APTCs) from architecture models using large language models, achieving up to 93% usefulness and 86% correctness in evaluation.

Software architecture models capture early design decisions that strongly influence system quality attributes, including security. However, architecture-level security assessment and feedback are often absent in practice, allowing security weaknesses to propagate into later phases of the software development lifecycle and, in some cases, to remain undiscovered, ultimately leading to vulnerable systems. In this paper, we bridge this gap by proposing the generation of Abstract Penetration Test Cases (APTCs) from software architecture models as an input to support architecture-level security assessment. We first introduce a metamodel that defines the APTC concept, and then investigate the use of large language models with different prompting strategies to generate meaningful APTCs from architecture models. To design the APTC metamodel, we analyze relevant standards and state of the art using two criteria: (i) derivability from software architecture, and (ii) usability for both architecture security assessment and subsequent penetration testing. Building on this metamodel, we then proceed to generate APTCs from software architecture models. Our evaluation shows promising results, achieving up to 93\% usefulness and 86\% correctness, indicating that the generated APTCs can substantially support both architects (by highlighting security-critical design decisions) and penetration testers (by providing actionable testing guidance).

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