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Hacking generative Ai

Track :

Computer Science

Course Presenter :

IBM Technology

Lessons no : 16

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What will you learn in this course?
  • Identify vulnerabilities in generative AI systems using prompt injection and jailbreak techniques for security testing and analysis
  • Develop strategies to exploit adversarial prompts and bypass safety filters in large language models like ChatGPT and DALL·E
  • Analyze data leakage risks and reverse engineer generative AI models to understand their behavior and potential security flaws
  • Design and simulate AI red teaming scenarios to evaluate the robustness and resilience of generative AI systems
  • Implement ethical hacking practices to assess security vulnerabilities while adhering to responsible AI development standards
  • Apply defensive countermeasures to mitigate exploits, protect sensitive data, and enhance the security of AI models
  • Evaluate the effectiveness of safety restrictions and ethical filters in preventing malicious prompts and model manipulation
  • Utilize practical skills to test, analyze, and improve the security posture of generative AI applications

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Lessons | 16


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Hacking generative Ai, in this course we will learn about the techniques and strategies used to analyze, test, and potentially exploit generative AI systems like ChatGPT, DALL·E, and other large language models. You'll explore real-world methods such as prompt injection, jailbreak attacks, and adversarial prompting, as well as how these methods can bypass ethical filters and safety restrictions. The course also covers data leakage risks, reverse engineering model behavior, and simulating AI red teaming scenarios. Throughout, we’ll emphasize ethical considerations and defensive countermeasures to build more secure AI systems. By the end of the course, you'll understand how generative models can be vulnerable—and how developers and security experts can protect them. Prepare to dive deep into the inner workings of generative AI and its security landscape. IBM Technology