Prompt Engineering: Covering Tracks with GenAI

About this course

As cyber threats become more sophisticated, the art of evading detection, covering one's tracks, and maintaining access becomes an essential craft for every ethical hacker. The potential of artificial intelligence (AI) to revolutionize clandestine operations in cybersecurity cannot be overlooked. This course examines the fusion of traditional stealth techniques in hacking with the cutting-edge capabilities of generative AI, looking at how generative AI can be harnessed to leave no digital footprint, ensuring prolonged access to compromised systems. You'll begin by exploring the techniques used by hackers to maintain access and the role of generative AI in detecting and mitigating attempts to cover tracks. You'll orchestrate a generative AI-assisted operation to cover tracks in a simulated environment and use generative AI to identify signs of advanced track-covering activities. Next, you'll identify the implications of failing to cover tracks, and of maintaining prolonged access to compromised systems. Lastly, you'll analyze and evaluate real-world case studies focusing on the potential impact of generative AI.

Learning objectives

• Discover the key concepts covered in this course
• Outline the importance of covering tracks and maintaining access in ethical hacking, focusing on generative ai's potential impact
• Identify techniques used by hackers to maintain access and how these techniques can be detected or enhanced with ai