Overview
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This specialization is intended for computer scientists and engineers wishing to expand their technical expertise to the realm of Computing Security, with a broad skill-set and understanding of offensive Cybersecurity. Regardless of what area of Computing you may want to specialize in – from networking and systems to algorithms in machine learning and AI – a deep understanding of how the underlying technologies work, and how they can be abused, is essential to a robustly functioning, secure computing environment. One thing we have learned from the remarkable history of Computing is that staying ahead of attackers requires adopting the adversarial mindset. We aim to develop this mindset through a series of three courses, each exploring a different realm of technology. Throughout the series, expect an in-depth technical treatment with little reliance on pre-made tooling, as we seek to create exploits from scratch. By completing the specialization, you will have gained exposure to modern attacks on computer networks, web applications, binary programs, and cutting-edge areas of research in subverting AI systems.
Syllabus
- Course 1: Security & Ethical Hacking: Attacking the Network
- Course 2: Security & Ethical Hacking: Attacking Unix and Windows
- Course 3: Security & Ethical Hacking: Attacking Web and AI Systems
Courses
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This course explains the science and art behind offensive security techniques used in penetration testing of networks and systems. A review of networking concepts is given. Students will utilize low-level programming through network interfaces, in executing a variety of network attacks, while learning to use essential auxiliary tooling for both recon and active attacks. An introduction to cryptogpahy for pentesters is provided. An understanding of python programming, C programming, and basic computer architecture is recommended. Programming experience is required. Familiarity with x86 Assembly (or some assembly language) is recommended. This course can be taken for academic credit as part of CU Boulder’s Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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This course explores the science and art of offensive security techniques used in penetration testing of networks and systems. Areas of focus include post-exploitation and exploitation of Unix (esp. Linux) machines/servers, and Windows OS. A basic review of relevant x86 Assembly language constructs will be given. Students will utilize scripting and low-level programming and other technical means to execute a variety of attacks in adversarial recon, lateral movement, privilege escalation, and authentication bypass on Unix systems, as well as active exploitation of remote memory corruption attacks on multiple OS. An introduction to general computer memory is given, along with other topics in operating systems, as needed. An understanding of C/C++ compiled program languages, code debugging, python programming, and basic computer architecture is required. Experience with Assembly Language programming (Intel) and UNIX command-line (scripting) is preferred. The course is geared towards students in Computer Science, Computer Engineering, and similar domains – but those with sufficient hours of experience in the topics mentioned will be able to follow the material. This course can be taken for academic credit as part of CU Boulder’s Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
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In this course you will learn how the security of web-based software, including deployed AI agents, can be compromised. Real-world attacks we study are conducted against a variety of web technologies and frameworks. In addition, we will introduce the topic of Adversarial Machine Learning (exploiting algorithms and learning techniques) in the Artificial Intelligence domain, including Language Models. We will review and study modern, cutting-edge research in this area. Course assessments are through quizzes, hands-on exercises and an exam. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Taught by
Ahmed M. Hamza