mlsanityData to 7 Oct 2026

A Survey on Offensive AI Within Cybersecurity

arXiv 2410.03566 ↗First posted 26 Sep 2024cs.CR cs.AIcited by 3

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Abstract (arXiv)

Artificial Intelligence (AI) has witnessed major growth and integration across various domains. As AI systems become increasingly prevalent, they also become targets for threat actors to manipulate their functionality for malicious purposes. This survey paper on offensive AI will comprehensively cover various aspects related to attacks against and using AI systems. It will delve into the impact of offensive AI practices on different domains, including consumer, enterprise, and public digital infrastructure. The paper will explore adversarial machine learning, attacks against AI models, infrastructure, and interfaces, along with offensive techniques like information gathering, social engineering, and weaponized AI. Additionally, it will discuss the consequences and implications of offensive AI, presenting case studies, insights, and avenues for further research.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 20 of its 97 references that are in the map. First posted on arXiv 26 Sep 2024.

Builds on

20 of 97 references.

References · 20

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8 more
  1. 2022On the Impossible Safety of Large AI Modelscited by 27
  2. 2020Memristors -- from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computingcited by 10
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  8. 2023Intell-dragonfly: A Cybersecurity Attack Surface Generation Engine Based On Artificial Intelligence-generated Content Technologycited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.