Generative AI and Prompt Engineering for Ethical Hacking Proficiency (Advanced Level)

  • 24m
  • 24 questions
The Generative AI and Prompt Engineering for Ethical Hacking Proficiency (Advanced Level) benchmark measures your advanced working understanding of many security-related issues, procedures, and tools and extended exposure to generative AI tools and best practices. A learner who scores high on this benchmark demonstrates a proficient understanding of ethical hacking and generative AI in several areas. They are considered a team leader and can work independently with minimal to no supervision.

Topics covered

  • assess real-world case studies involving network and perimeter hacking, focusing on the potential impact of generative AI
  • conduct a generative AI-assisted simulated hack on a cloud service
  • conduct a generative AI-assisted SQL injection attack in a simulated environment, explaining AI-aided countermeasures
  • describe different countermeasures against malware and social engineering attacks
  • describe how the same AI-informed measures used to safeguard networks can also be leveraged by malicious actors
  • describe the importance of network perimeter security and how generative AI strengthens this security
  • execute a generative AI-assisted mobile platform hack, showcasing AI-enhanced countermeasures
  • explore how to work with GPT models via the OpenAI ChatGPT web app and via the OpenAI API
  • identify real-world system hacking scenarios, with a focus on the role of generative AI
  • identify techniques used by hackers to maintain access and how these techniques can be detected or enhanced with AI
  • leverage generative AI to conduct an effective enumeration, highlighting the efficiency of AI-assisted techniques
  • outline how to educate users about the dangers of social engineering and the importance of training
  • outline how to evaluate web and database security solutions in light of the evolving threat landscape shaped by generative AI
  • outline how to use generative AI in the detection and mitigation of cloud and IoT-based threats
  • outline the impact of generative AI in improving or thwarting system hacking techniques
  • outline the importance of covering tracks and maintaining access in ethical hacking, focusing on generative AI's potential impact
  • outline the potential challenges and solutions in reconnaissance
  • outline the role of generative AI in detecting and mitigating attempts to cover tracks
  • outline the steps to prepare for the integration of generative AI in attacks
  • perform a simple ethical hacking exercise by leveraging generative AI and the OpenAI API to analyze threat intelligence
  • perform a simulated social engineering attack and describe how to counter it
  • use generative AI and prompt engineering techniques for sophisticated network vulnerability discovery
  • use generative AI to analyze information gathered using active reconnaissance
  • use generative AI to summarize information gathered using passive reconnaissance