PentestMCP: A Toolkit for Agentic Penetration Testing

Fuente: arXiv
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Main Authors: Ezetta, Zachary, Feng, Wu-chang
Format: Preprint
Published: 2025
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author Ezetta, Zachary
Feng, Wu-chang
author_facet Ezetta, Zachary
Feng, Wu-chang
contents Agentic AI is transforming security by automating many tasks being performed manually. While initial agentic approaches employed a monolithic architecture, the Model-Context-Protocol has now enabled a remote-procedure call (RPC) paradigm to agentic applications, allowing for the flexible construction and composition of multi-function agents. This paper describes PentestMCP, a library of MCP server implementations that support agentic penetration testing. By supporting common penetration testing tasks such as network scanning, resource enumeration, service fingerprinting, vulnerability scanning, exploitation, and post-exploitation, PentestMCP allows a developer to customize multi-agent workflows for performing penetration tests.
format Preprint
id arxiv_https___arxiv_org_abs_2510_03610
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PentestMCP: A Toolkit for Agentic Penetration Testing
Ezetta, Zachary
Feng, Wu-chang
Cryptography and Security
Artificial Intelligence
Agentic AI is transforming security by automating many tasks being performed manually. While initial agentic approaches employed a monolithic architecture, the Model-Context-Protocol has now enabled a remote-procedure call (RPC) paradigm to agentic applications, allowing for the flexible construction and composition of multi-function agents. This paper describes PentestMCP, a library of MCP server implementations that support agentic penetration testing. By supporting common penetration testing tasks such as network scanning, resource enumeration, service fingerprinting, vulnerability scanning, exploitation, and post-exploitation, PentestMCP allows a developer to customize multi-agent workflows for performing penetration tests.
title PentestMCP: A Toolkit for Agentic Penetration Testing
topic Cryptography and Security
Artificial Intelligence
url https://arxiv.org/abs/2510.03610