Securely Sharing Randomized Code that Flies


Address space layout randomization was a great role model, being a light-weight defense technique that could prevent early return-oriented programming attacks. Simple yet effective, address space layout randomization was quickly widely adopted. Conversely, today only a trickle of defense techniques arebeing integrated or adopted mainstream. As code reuse attacks have evolved in complexity, defenses have strived to keep up. However, to do so, many have had to take unfavorable tradeoffs like using background threads or protecting only a subset of sensitive code. In reality, these tradeoffs were unavoidable steps necessary to improve the strength of the state of the art. In this article, we present Mardu, an on-demand system-wide runtime re-randomization technique capable of scalable protection of application as well as shared library code that most defenses have forgone. We achieve code sharing with diversification by implementing reactive and scalable rather than continuous or one-time diversification. Enabling code sharing further removes redundant computation like tracking and patching, along with memory overheads required by prior randomization techniques. In its baseline state, the code transformations needed for Mardu security hardening incur a reasonable performance overhead of 5.5% on SPEC and minimal degradation of 4.4% in NGINX, demonstrating its applicability to both compute-intensive and scalable real-world applications. Even when under attack, Mardu only adds from less than 1% to up to 15% depending on application size and complexity.

In ACM Journal Digital Threats: Research and Practice (DTRAP)
Yeongjin Jang
Yeongjin Jang
Principal Software Engineer

My research interests include cybersecurity/hacking, automated vulnerability discovery/analysis, secure system design, and applied cryptography.