Generative AI and Prompt Engineering for Ethical Hacking Competency (Intermediate Level)

  • 24m
  • 24 questions
The Generative AI and Prompt Engineering for Ethical Hacking Competency (Intermediate Level) benchmark measures your on-the-job experience with basic security issues and generative AI tools. A learner who scores high on this benchmark demonstrates competency in many areas of ethical hacking and generative AI and can work somewhat independently on the topic areas with supervision.

Topics covered

  • conduct a generative AI-assisted SQL injection attack in a simulated environment, explaining AI-aided countermeasures
  • conduct a network scan using a popular scanning tool integrated with generative AI
  • describe different countermeasures against malware and social engineering attacks
  • describe how generative AI can streamline and augment the use of various tools for scanning and enumeration
  • describe the effectiveness of network security hardware and software against AI-enhanced attack
  • describe the potential damage caused by different types of malware and social engineering attacks
  • identify the potential risks and benefits of using generative AI technologies in ethical hacking
  • identify vulnerabilities in Internet of Things (IoT) devices
  • identify ways in which prompt engineering techniques can optimize scanning strategies and output
  • leverage prompt engineering to detect social engineering attacks
  • list common vulnerabilities in databases
  • outline best practices to prevent system hacking while considering the integration of generative AI
  • outline common database hacking techniques in the context of generative AI
  • outline ethical hacking and highlight its growing importance in the context of advancements in generative AI technologies
  • outline how generative AI and prompt engineering can be applied to enhance the security of web applications and databases
  • outline how generative AI and prompt engineering could potentially exploit or mitigate database vulnerabilities
  • outline how generative AI can contribute to IoT device exploitation or protection
  • outline how generative AI technologies present both challenges and opportunities in the field of ethical hacking
  • outline how mobile platform hacking techniques can be enhanced using generative AI
  • provide an overview of how generative AI can play a role in each phase of the hacking process including reconnaissance, scanning, gaining access, maintaining access, and covering tracks
  • recognize how generative AI could help mitigate or exploit mobile vulnerabilities, focusing on mitigation techniques
  • 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