1. "10 Innovative Ways Hackers Will Leverage Machine Learning for Attacks"
2. "How Cybercriminals Will Exploit Machine Learning: 10 Potential Attack Methods"
3. "10 Strategies Hackers Might Employ with Machine Learning for Cyber Attacks"
4. "The Dark Side of AI: 10 Ways Hackers Could Utilize Machine Learning in Attacks"
5. "Exploiting Algorithms: 10 Tactics Hackers Could Use Machine Learning to Attack"
6. "10 Ways Machine Learning Could Empower Hackers in Cyber Attacks"
7. "The Future of Cybercrime: 10 Ways Hackers Will Harness Machine Learning"
8. "10 Techniques Hackers May Use Machine Learning to Enhance Their Attacks"
9. "Revealing Risks: 10 Ways Machine Learning Could Be Weaponized by Hackers"
10. "10 Potential Attack Vectors Where Hackers Will Apply Machine Learning"

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A recent survey by Bugcrowd reveals a growing trend among hackers, showing that 62% utilize artificial intelligence for data analysis, 61% for task automation, and 38% for detecting vulnerabilities.

7. Autonomous agents

In scenarios where an enterprise faces a cyberattack, immediate action such as disconnecting affected systems from the internet can hinder malware from accessing its command-and-control servers to receive further instructions. Kantarcioglu points out that attackers are likely to develop sophisticated models capable of maintaining a presence even in the absence of direct control. This enables longer persistence within the compromised systems.

The availability of autonomous agents has expanded significantly, with commercial solutions from companies like Microsoft, along with various open-source platforms lacking sufficient safeguards against malicious use. Scanlon from CMU notes that historically, adversaries relied on human involvement for executing attacks, which typically required multiple steps. However, the ability to deploy autonomous agents to handle these tasks represents a substantial threat, underscoring that this capability facilitated by AI has transitioned from potential to reality.

Source
www.csoonline.com