How to Integrate Artificial Intelligence on Audio Files into Offensive Security Workflows

INTRODUCTION

Open source intelligence, commonly known as OSINT, refers to the process of collecting, processing and analyzing information from publicly available sources in order to generate actionable information that can be used for concrete actions, also known as actionable intelligence. OSINT involves various types of data from multiple sources, such as television, radio, print, or the Internet, such as TikTok, YouTube and other social networks.

The very advantage of being able to access thousands of public and open sources of information is at the same time its biggest problem: how to separate the important from the accessory or simply irrelevant.

This article focuses on how Artificial Intelligence capabilities, such as machine learning and natural language processing, can be leveraged to improve data analysis on audiovisual documents. These techniques enable entity recognition, information classification, sentiment detection and anomaly identification, helping analysts to extract valuable insights and make informed decisions.

TAKING ADVANTAGE OF THE VOICE FILES AND AUDIO TRACKS IN OSINT:

Up until recently, the use of voice files and audio tracks in OSINT was relatively limited due to the challenges associated with transcribing and analyzing this type of content. Manual transcription required considerable effort, time and specialized resources, making it costly and impractical for comprehensive analysis of large volumes of voice files.

However, with the advancement of artificial intelligence tools and Natural Language Processing (NLP), a significant change has occurred. Artificial intelligence-based speech recognition and automatic transcription techniques have greatly improved....