A Taxonomy of Pix Fraud in Brazil: Attack Methodologies, AI-Driven Amplification, and Defensive Strategies

TL;DR

This paper reviews and classifies Pix fraud attack methods in Brazil, highlighting their evolution and emphasizing the need for adaptive security measures and user awareness to combat increasingly sophisticated schemes.

Contribution

It provides a comprehensive taxonomy of Pix fraud techniques, combining literature review and industry insights to identify evolving attack strategies and propose targeted defensive approaches.

Findings

Fraud schemes have evolved from social engineering to hybrid strategies.

Security measures must adapt to increasing attack sophistication.

Continuous user awareness is essential for effective defense.

Abstract

This work presents a review of attack methodologies targeting Pix, the instant payment system launched by the Central Bank of Brazil in 2020. The study aims to identify and classify the main types of fraud affecting users and financial institutions, highlighting the evolution and increasing sophistication of these techniques. The methodology combines a structured literature review with exploratory interviews conducted with professionals from the banking sector. The results show that fraud schemes have evolved from purely social engineering approaches to hybrid strategies that integrate human manipulation with technical exploitation. The study concludes that security measures must advance at the same pace as the growing complexity of attack methodologies, with particular emphasis on adaptive defenses and continuous user awareness.