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arXiv preprint arXiv:2402.00891 (2024), https://arxiv.org/pdf/2402.00891

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

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background 2

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cs.CR 2 cs.CE 1

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2026 3

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UNVERDICTED 3

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background 2

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background 2

representative citing papers

Towards Automated Pentesting with Large Language Models

cs.CR · 2026-04-13 · unverdicted · novelty 5.0

RedShell fine-tunes LLMs on enhanced malicious PowerShell data to produce syntactically valid offensive code for pentesting, reporting over 90% validity, strong semantic match to references, and better edit-distance similarity than prior methods plus functional execution success.

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Showing 3 of 3 citing papers.