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Yu Ding

Yu Ding

Yu Ding is a staff software engineer at Google Research, and previously a principal security scientist at Baidu Research Institute. His areas of interest include system security, programming languages and confidential computing.
Authored Publications
Google Publications
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    Broadly Enabling KLEE to Effortlessly Find Unrecoverable Errors
    Ying Zhang
    Peng Li
    Lingxiang Wang
    Na Meng
    Dan Williams
    (2024)
    Preview abstract Rust is a general-purpose programming language designed for performance and safety. Unrecoverable errors (e.g., Divide by Zero) in Rust programs are critical, as they signal bad program states and terminate programs abruptly. Previous work has contributed to utilizing KLEE, a dynamic symbolic test engine, to verify the program would not panic. However, it is difficult for engineers who lack domain expertise to write test code correctly. Besides, the effectiveness of KLEE in finding panics in production Rust code has not been evaluated. We created an approach, called PanicCheck, to hide the complexity of verifying Rust programs with KLEE. Using PanicCheck, engineers only need to annotate the function-to-verify with #[panic_check]. The annotation guides PanicCheck to generate test code, compile the function together with tests, and execute KLEE for verification. After applying PanicCheck to 21 open-source and 2 closed-source projects, we found 61 test inputs that triggered panics; 60 of the 61 panics have been addressed by developers so far. Our research shows promising verification results by KLEE, while revealing technical challenges in using KLEE. Our experience will shed light on future practice and research in program verification. View details
    PTStore: Lightweight Architectural Support for Page Table Isolation
    Wende Tan
    Yangyu Chen
    Yuan Li
    Ying Liu
    Jianping Wu
    Chao Zhang
    2023 60th ACM/IEEE Design Automation Conference (DAC), IEEE, pp. 1-6
    Preview abstract Page tables are critical data structures in kernels, serving as the trust base of most mitigation solutions. Their integrity is thus crucial but is often taken for granted. Existing page table protection solutions usually provide insufficient security guarantees, require heavy hardware, or introduce high overheads. In this paper, we present a novel lightweight hardware-software co-design solution, PTStore, consisting of a secure region storing page tables and tokens verifying page table pointers. Evaluation results on FPGA-based prototypes show that PTStore only introduces <0.92% hardware overheads and <0.86% performance overheads, but provides strong security guarantees, showing that PTStore is efficient and effective. View details
    Building and maintaining a third-party library supply chain for productive and secure SGX enclave development
    Mingshen Sun
    Huibo Wang
    Tongxin Li
    Rundong Zhou
    Zhaofeng Chen
    Yiming Jing
    Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Software Engineering in Practice (2020), pp. 100-109
    Preview abstract The big data industry is facing new challenges as concerns about privacy leakage soar. One of the remedies to privacy breach incidents is to encapsulate computations over sensitive data within hardware-assisted Trusted Execution Environments (TEE). Such TEE-powered software is called secure enclaves. Secure enclaves hold various advantages against competing for privacy-preserving computation solutions. However, enclaves are much more challenging to build compared with ordinary software. The reason is that the development of TEE software must follow a restrictive programming model to make effective use of strong memory encryption and segregation enforced by hardware. These constraints transitively apply to all third-party dependencies of the software. If these dependencies do not officially support TEE hardware, TEE developers have to spend additional engineering effort in porting them. High development and maintenance cost is one of the major obstacles against adopting TEE-based privacy protection solutions in production. In this paper, we present our experience and achievements with regard to constructing and continuously maintaining a third-party library supply chain for TEE developers. In particular, we port a large collection of Rust third-party libraries into Intel SGX, one of the most mature trusted computing platforms. Our supply chain accepts upstream patches in a timely manner with SGX-specific security auditing. We have been able to maintain the SGX ports of 159 open-source Rust libraries with reasonable operational costs. Our work can effectively reduce the engineering cost of developing SGX enclaves for privacy-preserving data processing and exchange. View details
    Towards Memory Safe Enclave Programming with Rust-SGX
    Huibo Wang
    Mingshen Sun
    Yiming Jing
    Ran Duan
    Long Li
    Yulong Zhang
    Tao Wei
    Zhiqiang Lin
    Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security (2019), pp. 2333-2350
    Preview abstract Intel Software Guard eXtension (SGX), a hardware supported trusted execution environment (TEE), is designed to protect security critical applications. However, it does not terminate traditional memory corruption vulnerabilities for the software running inside enclave, since enclave software is still developed with type unsafe languages such as C/C++. This paper presents RUST-SGX, an efficient and layered approach to exterminating memory corruption for software running inside SGX enclaves. The key idea is to enable the development of enclave programs with an efficient memory safe system language Rust with a RUST-SGX SDK by solving the key challenges of how to (1) make the SGX software memory safe and (2) meanwhile run as efficiently as with the SDK provided by Intel. We therefore propose to build RUST-SGX atop Intel SGX SDK, and tame unsafe components with formally proven memory safety. We have implemented RUST-SGX and tested with a series of benchmark programs. Our evaluation results show that RUST-SGX imposes little extra overhead (less than 5% with respect to the SGX specific features and services compared to software developed by Intel SGX SDK), and meanwhile have stronger memory safety. View details
    VTrust: Regaining Trust on Virtual Calls
    Chao Zhang
    Scott A. Carr
    Tongxin Li
    Chenyu Song
    Mathias Payer
    Dawn Song
    The Network and Distributed System Security Symposium (NDSS'16) (2016)
    Preview abstract Virtual function calls are one of the most popular control-flow hijack attack targets. Compilers use a virtual function pointer table, called a VTable, to dynamically dispatch virtual function calls. These VTables are read-only, but pointers to them are not. VTable pointers reside in objects that are writable, allowing attackers to overwrite them. As a result, attackers can divert the control-flow of virtual function calls and launch VTable hijacking attacks. Researchers have proposed several solutions to protect virtual calls. However, they either incur high performance overhead or fail to defeat some VTable hijacking attacks. In this paper, we propose a lightweight defense solution, VTrust, to protect all virtual function calls from VTable hijacking attacks. It consists of two independent layers of defenses: virtual function type enforcement and VTable pointer sanitization. Combined with modern compilers’ default configuration, i.e., placing VTables in read-only memory, VTrust can defeat all VTable hijacking attacks and supports modularity, allowing us to harden applications module by module. We have implemented a prototype on the LLVM compiler framework. Our experiments show that this solution only introduces a low performance overhead, and it defeats real world VTable hijacking attacks. View details
    Android Low Entropy Demystified
    Zhuo Peng
    Yuanyuan Zhou
    Chao Zhang
    IEEE International Conference on Communications (ICC) (2014)
    Preview abstract We look into the issue that the amount of entropy kept by the pseudorandom number generator (PRNG) of Android is constantly low. We find that the accusation against this issue of causing poor performance and low frame rate experienced by users is ungrounded. We also investigate possible security vulnerabilities resulting from this issue. We find that this issue does not affect the quality of random numbers that are generated by the PRNG and used in Android applications because recent Android devices do not lack entropy sources. However, we identify a vulnerability in which the stack canary for all future Android applications is generated earlier than the PRNG is properly setup. This vulnerability makes stack overflow simpler and threats Android applications linked with native code (through NDK) as well as Dalvik VM instances. An attacker could nullify the stack protecting mechanism, given the knowledge of the time of boot or a malicious app running on the victim device. This vulnerability also affects the address space layout randomization (ASLR) mechanism on Android, and can turn it from a weak protection to void. We discuss in this paper several possible attacks against this vulnerability as well as ways of defending. As this vulnerability is rooted in an essential Android design choice since the very first version, it is difficult to fix. View details
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