Unlocking Insights: An Extensible Framework for Automated Metadata Extraction from Online Documents

Information Gathering is a fundamental stage in a typical Penetration Testing (PT) process, in which penetration testers collect as much information as possible regarding a target system to uncover vulnerabilities, threats, and security issues. Metadata extraction plays an important role in this stage since it can reveal significant details about the target system, such as used technologies, software versions, user information, and network data, which can expose potential attack vectors. This paper introduces a novel framework for automated metadata extraction from documents linked within a specified web page. The framework is designed to streamline Information Gathering processes by offering an easy-to-use, integrated, extensible, and flexible solution. Our proposal can be effective in uncovering information that is not immediately visible to a penetration tester, giving them a greater chance of success in identifying the most fruitful attack patterns.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/trustcom63139.2024.00209
Primary Topic
Semantic Web and Ontologies
Type
article
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article

Unlocking Insights: An Extensible Framework for Automated Metadata Extraction from Online Documents

Francesco Palmieri, Arcangelo Castiglione, Raffaele Pizzolante
Semantic Web and Ontologies
article

Unlocking Insights: An Extensible Framework for Automated Metadata Extraction from Online Documents

Francesco Palmieri, Arcangelo Castiglione, Raffaele Pizzolante
article en

Abstract

Information Gathering is a fundamental stage in a typical Penetration Testing (PT) process, in which penetration testers collect as much information as possible regarding a target system to uncover vulnerabilities, threats, and security issues. Metadata extraction plays an important role in this stage since it can reveal significant details about the target system, such as used technologies, software versions, user information, and network data, which can expose potential attack vectors. This paper introduces a novel framework for automated metadata extraction from documents linked within a specified web page. The framework is designed to streamline Information Gathering processes by offering an easy-to-use, integrated, extensible, and flexible solution. Our proposal can be effective in uncovering information that is not immediately visible to a penetration tester, giving them a greater chance of success in identifying the most fruitful attack patterns.

University of Salerno (IT)
Openalex Percentile: Top 74%
Semantic Web and Ontologies
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Unlocking Insights: An Extensible Framework for Automated Metadata Extraction from Online Documents — Francesco Palmieri, Arcangelo Castiglione, et al. · (2024) | TGRS Research Map | TGRS