Final Exam: Prompt Engineering for Ethical Hacking

WHAT YOU WILL LEARN

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  Outline the concept of generative ai and prompt engineering and its application in ethical hacking scenarios
  

  perform a simple ethical hacking exercise by leveraging generative ai and the openai api to analyze threat intelligence
  

  outline the role of an ethical hacker in today's digital landscape, particularly when interacting with generative ai technologies
  

  outline the importance of maintaining high ethical standards when using powerful tools like generative ai in ethical hacking
  

  outline the steps to prepare for the integration of generative ai in attacks
  

  use generative ai technologies to identify potential attacks
  

  identify reconnaissance techniques and describe the differences between active and passive reconnaissance
  

  list different methods and tools used for reconnaissance
  

  identify the benefits that reconnaissance provides for the ethical hacking process
  

  use generative ai to summarize information gathered using passive reconnaissance
  

  outline how to protect systems and networks from reconnaissance
  

  apply prompt engineering to enhance the effectiveness of reconnaissance techniques
  

  describe how generative ai can streamline and augment the use of various tools for scanning and enumeration
  

  identify ways in which prompt engineering techniques can optimize scanning strategies and output
  

  analyze and evaluate the potentially enriched information obtained from ai-assisted scanning and enumeration
  

  describe how the same ai-informed measures used to safeguard networks can also be leveraged by malicious actors
  

  distinguish between various scanning techniques (port scanning, network scanning, and vulnerability scanning), and describe how each can be boosted by generative ai
  

  analyze case studies involving scanning and enumeration techniques, with a focus on the role of generative ai in these real-world scenarios
  

  outline how generative ai can be used to enhance password cracking, privilege escalation, and application execution
  

  outline best practices to prevent system hacking while considering the integration of generative ai
  

  recognize how generative ai can help fortify cybersecurity defenses against system hacking
  

  test the security of a system utilizing generative ai to drive the process
  

  outline the impact of generative ai in improving or thwarting system hacking techniques
  

  leverage generative ai to report system vulnerabilities and recommend steps for mitigation
  

  describe the various types of malware including viruses, worms, trojans, and ransomware
  

  outline the principles and techniques of social engineering
  

  leverage prompt engineering to detect social engineering attacks
  

  describe the potential damage caused by different types of malware and social engineering attacks
  

  describe different countermeasures against malware and social engineering attacks
  

  describe real-world case studies involving malware and social engineering
• 

  describe the fundamentals of network and perimeter hacking
  

  describe how generative ai can enhance various types of attack
  

  use generative ai and prompt engineering techniques for sophisticated network vulnerability discovery
  

  describe the importance of network perimeter security and how generative ai strengthens this security
  

  describe how generative ai and prompt engineering can help uncover vulnerabilities in a wireless network
  

  conduct a simulated generative ai-driven attack on a wired network, highlighting ai-enhanced prevention methods
  

  describe common vulnerabilities in web applications
  

  describe common vulnerabilities in databases
  

  outline common database hacking techniques in the context of generative ai and how these techniques may evolve or be defended against using ai technologies
  

  conduct a generative ai-assisted sql injection attack in a simulated environment, explaining ai-aided countermeasures
  

  describe strategies to secure web applications and databases, focusing on how generative ai and prompt engineering can bolster these strategies
  

  employ generative ai and prompt engineering to detect and address vulnerabilities in a web application
  

  describe the importance of regular updates and patches in web and database security in the context of ai-driven threats
  

  identify vulnerabilities in cloud services
  

  describe hacking methods specific to cloud services and iot devices
  

  outline how to use generative ai in the detection and mitigation of cloud and iot-based threats
  

  outline best practices for securing cloud services and iot devices, emphasizing the role of generative ai
  

  evaluate security measures for cloud services and iot devices and ai's potential for both attack and defense
  

  outline trends and advancements in cloud and iot security and the role of generative ai
  

  describe common vulnerabilities in mobile platforms
  

  describe mobile platform hacking techniques in the context of generative ai
  

  execute a generative ai-assisted mobile platform attack, showcasing ai-enhanced countermeasures
  

  develop strategies to educate users about the role of ai in mobile platform security
  

  describe potential impacts of mobile platform hacking in an era of ai-driven threats
  

  describe the importance of regular updates and patches in mobile platform security in an era of ai-driven threats
  

  outline techniques used by hackers to maintain access, analyzing how these techniques can be detected or enhanced with ai
  

  describe the role of generative ai in detecting and mitigating attempts to cover tracks
  

  list the potential impacts of not properly covering tracks on a hacking operation
  

  use generative ai to identify signs of advanced track-covering activities
  

  describe the implications of maintaining prolonged access to compromised systems