Citation

Gan, Jing Hwan and Lim, Tek Yong (2026) SHARKAPT: An Autonomous LLM-Orchestrated Penetration Testing Framework with MCP-Based Tool Integration. In: 23rd International Joint Conference on Computer Science and Software Engineering, JCSSE 2026, 24 June 2026 - 27 June 2026, Bangkok.

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Abstract

Penetration testing is still highly dependent on trained professionals (who are required to manually coordinate heterogeneous security tools, multi-phase findings, and actionable reports) that is both time-consuming, expertiseoriented and inadequate to the speed of current threats. The framework described in this paper, SHARKAPT, is an autonomous AI-based penetration testing framework that uses the Model Context Protocol and large language model orchestration to conduct end-to-end automated security testing of both network and web application-related systems. SHARKAPT uses a multi-agent architecture based on LangGraph with five specialised agents: reconnaissance, network penetration testing, web application testing, exploitation as well as report generation and a decision engine that dynamically chooses 60+ real-world security tools. Google Gemini 3.1 Pro evaluated empirically against Metasploitable2 and OWASP Juice Shop has coverage of 71.7% of the Open Web Application Security Project Top 10 2021 challenges (9/10 categories), 79.1% Metasploitable2 known-vulnerability coverage, a 99.1% step success rate on the web session (111 steps), and a 94.5% step success rate on the network session (73 steps). All finding results are rated using a deterministic CVSS v3.0 calculator and stored in organised HTML reports containing per-finding evidence.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Autonomous security testing
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	31 Jul 2026 07:20
Last Modified:	31 Jul 2026 07:20
URII:	http://shdl.mmu.edu.my/id/eprint/16433

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