Isil Dillig
University of Texas at Austin, TX·Computer Science
Every time a web page runs, the browser turns its JavaScript code into fast machine code on the fly. The tool that does this is a just-in-time (JIT) compiler.
- Fields
Computer Science
- Topics
JavaScript
just-in-time compilation
JIT compiler
- Grants
- 1 known grant, through Sep 2027
What they work on
- Evaluate the security of JavaScript just-in-time (JIT) compilers through empirical study, to find which components are most open to attack and which matter most for browser speed.
- Formalize what security and correctness mean for different parts of a JIT compiler, giving precise definitions that code can be proven to satisfy.
- Modify and extend existing browser JIT compilers to find and fix bugs, and provide formal security guarantees for components that attackers target today.
- Design and build new JavaScript interpreters and compilers that are extensible, maintainable and secure by construction, rethinking how browsers run JavaScript.
More about the research
Bugs in these compilers have become the single largest threat to web security. Attackers have exploited them to target users, including at-risk groups. The project asks how to build JIT compilers that are provably secure, without the high cost and long timelines usually needed for high-assurance software.
Why it matters
Hundreds of millions of people browse the web daily on browsers whose JavaScript compilers are a leading target for attackers. Provably secure compilers that are practical to build could shrink this attack surface. That would protect everyday users, including marginalized and at-risk people who have been targeted through these bugs.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Deian Stefan
University of California-San Diego, CA·Computer Science
Build static analysis tools for the Rust ecosystem that work with human auditors to detect, triage and classify weaknesses in foreign function interfaces between Rust and C/C++.
Tegan Brennan
Stevens Institute of Technology, NJ·Computer Science·Early-career
Mark just-in-time compiler optimizations capable of introducing side-channel vulnerabilities, using taint analysis that tracks the flow of sensitive data through a program.
Milijana Surbatovich
University of Maryland, MD·Computer Science·Early-career
Develop the first formal model of an intermittence-safe operating system, with defined abstraction layers that separate tiers of trust and allow each component to be verified on its own.
The school
University of Texas at Austin: 49 labs on PI Pages, $1.1B a year on research, 871 research doctorates a year.
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