# Red Teaming with Artificial Intelligence-Driven Cyberattacks: A Scoping Review

arXiv: https://arxiv.org/abs/2503.19626 · HTML: https://mlsanity.com/paper/2503.19626/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 37 references that are in the map.
- First posted on arXiv 25 Mar 2025.

## Builds on (most cited first, 5 of 5)

- [The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation](https://mlsanity.com/paper/1802.07228/) (2018)
- [Spear Phishing With Large Language Models](https://mlsanity.com/paper/2305.06972/) (2023)
- [The Shadow of Fraud: The Emerging Danger of AI-powered Social Engineering and its Possible Cure](https://mlsanity.com/paper/2407.15912/) (2024)
- [Unethical Research: How to Create a Malevolent Artificial Intelligence](https://mlsanity.com/paper/1605.02817/) (2016)
- [A Systematic Review of Machine Learning Enabled Phishing](https://mlsanity.com/paper/2310.06998/) (2023)

## Abstract (arXiv)

The progress of artificial intelligence (AI) has made sophisticated methods available for cyberattacks and red team activities. These AI attacks can automate the process of penetrating a target or collecting sensitive data. The new methods can also accelerate the execution of the attacks. This review article examines the use of AI technologies in cybersecurity attacks. It also tries to describe typical targets for such attacks. We employed a scoping review methodology to analyze articles and identify AI methods, targets, and models that red teams can utilize to simulate cybercrime. From the 470 records screened, 11 were included in the review. Various cyberattack methods were identified, targeting sensitive data, systems, social media profiles, passwords, and URLs. The application of AI in cybercrime to develop versatile attack models presents an increasing threat. Furthermore, AI-based techniques in red team use can provide new ways to address these issues.