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

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