Taemin Park (University of California, Irvine), Karel Dhondt (imec-DistriNet, KU Leuven), David Gens (University of California, Irvine), Yeoul Na (University of California, Irvine), Stijn Volckaert (imec-DistriNet, KU Leuven), Michael Franz (University of California, Irvine, USA)

Data-only attacks against dynamic scripting environments have become common. Web browsers and other modern applications embed scripting engines to support interactive content. The scripting engines optimize performance via just-in-time compilation. Since applications are increasingly hardened against code-reuse attacks, adversaries are looking to achieve code execution or elevate privileges by corrupting sensitive data like the intermediate representation of optimizing JIT compilers. This has inspired numerous defenses for just-in-time compilers.

Our paper demonstrates that securing JIT compilation is not sufficient. First, we present a proof-of-concept data-only attack against a recent version of Mozilla’s SpiderMonkey JIT in which the attacker only corrupts heap objects to successfully issue a system call from within bytecode execution at run time. Previous work assumed that bytecode execution is safe by construction since interpreters only allow a narrow set of benign instructions and bytecode is always checked for validity before execution. We show that this does not prevent malicious code execution in practice. Second, we design a novel defense, dubbed NoJITsu to protect complex, real-world scripting engines from data-only attacks against interpreted code. The key idea behind our defense is to allow fine-grained memory access control by analyzing, identifying, isolating, and protecting individual memory regions focusing on their role in code generation at any point in the JavaScript engine. For this we combine automated analysis and instrumentation, compartmentalization, and Intel’s Memory-Protection Keys to secure SpiderMonkey against previous and our new attack. We implement and thoroughly test our implementation using a number of real-world scenarios as well as standard benchmarks. We show that NoJITsu successfully thwarts code-reuse as well as data-only attacks against any part of the scripting engine while offering a modest run-time overhead of only 5%.

View More Papers

PhantomCache: Obfuscating Cache Conflicts with Localized Randomization

Qinhan Tan (Zhejiang University), Zhihua Zeng (Zhejiang University), Kai Bu (Zhejiang University), Kui Ren (Zhejiang University)

Read More

When Match Fields Do Not Need to Match: Buffered...

Jiahao Cao (Tsinghua University; George Mason University), Renjie Xie (Tsinghua University), Kun Sun (George Mason University), Qi Li (Tsinghua University), Guofei Gu (Texas A&M University), Mingwei Xu (Tsinghua University)

Read More

Unicorn: Runtime Provenance-Based Detector for Advanced Persistent Threats

Xueyuan Han (Harvard University), Thomas Pasquier (University of Bristol), Adam Bates (University of Illinois at Urbana-Champaign), James Mickens (Harvard University), Margo Seltzer (University of British Columbia)

Read More

Bobtail: Improved Blockchain Security with Low-Variance Mining

George Bissias (University of Massachusetts Amherst), Brian N. Levine (University of Massachusetts Amherst)

Read More