PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI

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Hauptverfasser: Al-Sinani, Haitham S., Mitchell, Chris J.
Format: Preprint
Veröffentlicht: 2025
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author Al-Sinani, Haitham S.
Mitchell, Chris J.
author_facet Al-Sinani, Haitham S.
Mitchell, Chris J.
contents Ethical hacking today relies on highly skilled practitioners executing complex sequences of commands, which is inherently time-consuming, difficult to scale, and prone to human error. To help mitigate these limitations, we previously introduced 'PenTest++', an AI-augmented system combining automation with generative AI supporting ethical hacking workflows. However, a key limitation of PenTest++ was its lack of support for privilege escalation, a crucial element of ethical hacking. In this paper we present 'PenTest2.0', a substantial evolution of PenTest++ supporting automated privilege escalation driven entirely by Large Language Model reasoning. It also incorporates several significant enhancements: 'Retrieval-Augmented Generation', including both one-line and offline modes; 'Chain-of-Thought' prompting for intermediate reasoning; persistent 'PenTest Task Trees' to track goal progression across turns; and the optional integration of human-authored hints. We describe how it operates, present a proof-of-concept prototype, and discuss its benefits and limitations. We also describe application of the system to a controlled Linux target, showing it can carry out multi-turn, adaptive privilege escalation. We explain the rationale behind its core design choices, and provide comprehensive testing results and cost analysis. Our findings indicate that 'PenTest2.0' represents a meaningful step toward practical, scalable, AI-automated penetration testing, whilst highlighting the shortcomings of generative AI systems, particularly their sensitivity to prompt structure, execution context, and semantic drift, reinforcing the need for further research and refinement in this emerging space. Keywords: AI, Ethical Hacking, Privilege Escalation, GenAI, ChatGPT, LLM (Large Language Model), HITL (Human-in-the-Loop)
format Preprint
id arxiv_https___arxiv_org_abs_2507_06742
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
Al-Sinani, Haitham S.
Mitchell, Chris J.
Cryptography and Security
Ethical hacking today relies on highly skilled practitioners executing complex sequences of commands, which is inherently time-consuming, difficult to scale, and prone to human error. To help mitigate these limitations, we previously introduced 'PenTest++', an AI-augmented system combining automation with generative AI supporting ethical hacking workflows. However, a key limitation of PenTest++ was its lack of support for privilege escalation, a crucial element of ethical hacking. In this paper we present 'PenTest2.0', a substantial evolution of PenTest++ supporting automated privilege escalation driven entirely by Large Language Model reasoning. It also incorporates several significant enhancements: 'Retrieval-Augmented Generation', including both one-line and offline modes; 'Chain-of-Thought' prompting for intermediate reasoning; persistent 'PenTest Task Trees' to track goal progression across turns; and the optional integration of human-authored hints. We describe how it operates, present a proof-of-concept prototype, and discuss its benefits and limitations. We also describe application of the system to a controlled Linux target, showing it can carry out multi-turn, adaptive privilege escalation. We explain the rationale behind its core design choices, and provide comprehensive testing results and cost analysis. Our findings indicate that 'PenTest2.0' represents a meaningful step toward practical, scalable, AI-automated penetration testing, whilst highlighting the shortcomings of generative AI systems, particularly their sensitivity to prompt structure, execution context, and semantic drift, reinforcing the need for further research and refinement in this emerging space. Keywords: AI, Ethical Hacking, Privilege Escalation, GenAI, ChatGPT, LLM (Large Language Model), HITL (Human-in-the-Loop)
title PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
topic Cryptography and Security
url https://arxiv.org/abs/2507.06742