Whereas user-facing applications are often written in modern languages, the firmware, operating system, support libraries, and virtual machines that underpin just about any modern computer system are still written in low-level languages that value flexibility and performance over convenience and safety. Programming errors in low-level code are often exploitable and can, in the worst case, give adversaries unfettered access to the compromised host system. This book provides an introduction to and overview of automatic software diversity techniques that, in one way or another, use randomization to greatly increase the difficulty of exploiting the vast amounts of low-level code in existence. Diversity-based defenses are motivated by the observation that a single attack will fail against multiple targets with unique attack surfaces. We introduce the many, often complementary, ways that one can diversify attack surfaces and provide an accessible guide to more than two decades worth of research on the topic. We also discuss techniques used in conjunction with diversity to prevent accidental disclosure of randomized program aspects and present an in-depth case study of one of our own diversification solutions.

Whereas user-facing applications are often written in modern languages, the firmware, operating system, support libraries, and virtual machines that underpin just about any modern computer system are still written in low-level languages that value flexibility and performance over convenience and safety. Programming errors in low-level code are often exploitable and can, in the worst case, give adversaries unfettered access to the compromised host system. This book provides an introduction to and overview of automatic software diversity techniques that, in one way or another, use randomization to greatly increase the difficulty of exploiting the vast amounts of low-level code in existence. Diversity-based defenses are motivated by the observation that a single attack will fail against multiple targets with unique attack surfaces. We introduce the many, often complementary, ways that one can diversify attack surfaces and provide an accessible guide to more than two decades worth of research on the topic. We also discuss techniques used in conjunction with diversity to prevent accidental disclosure of randomized program aspects and present an in-depth case study of one of our own diversification solutions.