LLM-Based Agents for Software and Systems Security: Approaches, Applications, and Assessment
Paper recorded by Signals 4 on 2026-08-28 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-08-28 on arXiv · recorded by Signals 4 on 2026-08-31
Category: cs.AI · 人工智能 · first seen 2026-08-31
Abstract
Software and systems security workflows are typically procedural: analysts inspect heterogeneous artifacts, form hypotheses, invoke tools, interpret outputs, and revise plans. Large language model (LLM)-based agents, which can plan, use tools, retain state, and revise actions across multi-step workflows, are being rapidly adopted to automate this work. Given the consequences of delegating security
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Cite this page: LLM-Based Agents for Software and Systems Security: Approaches, Applications, and Assessment: the #294 most recent of 300 cs.AI papers we have recorded (as of 2026-08-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/llm-based-agents-for-software-and-systems-security-approaches-applications-and-a.html
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