Hengkai Ye (The Pennsylvania State University), Hong Hu (The Pennsylvania State University)

Code injection was a favored technique for attackers to exploit buffer overflow vulnerabilities decades ago. Subsequently, the widespread adoption of lightweight solutions like write-xor-execute (W⊕X) effectively mitigated most of these attacks by disallowing writable-and-executable memory. However, we observe multiple concerning cases where software developers accidentally disabled W⊕X and reintroduced executable stacks to popular applications. Although each violation has been properly fixed, a lingering question remains: what underlying factors contribute to these recurrent mistakes among developers, even in contemporary software development practices?

In this paper, we conduct two investigations to gain a comprehensive understanding of the challenges associated with properly enforcing W⊕X in Linux systems. First, we delve into program-hardening tools to assess whether experienced security developers consistently catch the necessary steps to avoid executable stacks. Second, we analyze the enforcement of W⊕X on Linux by inspecting the source code of the compilation toolchain, the kernel, and the loader. Our investigation reveals that properly enforcing W⊕X on Linux requires close collaboration among multiple components. These tools form a complex chain of trust and dependency to safeguard the program stack. However, developers, including security researchers, may overlook the subtle yet essential .note.GNU-stack section when writing assembly code for various purposes, and inadvertently introduce executable stacks. For example, 11 program-hardening tools implemented as inlined reference monitors (IRM) introduce executable stacks to all “hardened” applications. Based on these findings, we discuss potential exploitation scenarios by attackers and provide suggestions to mitigate this issue.

View More Papers

BumbleBee: Secure Two-party Inference Framework for Large Transformers

Wen-jie Lu (Ant Group), Zhicong Huang (Ant Group), Zhen Gu (Alibaba Group), Jingyu Li (Ant Group & Zhejiang University), Jian Liu (Zhejiang University), Cheng Hong (Ant Group), Kui Ren (Zhejiang University), Tao Wei (Ant Group), WenGuang Chen (Ant Group)

Read More

Try to Poison My Deep Learning Data? Nowhere to...

Yansong Gao (The University of Western Australia), Huaibing Peng (Nanjing University of Science and Technology), Hua Ma (CSIRO's Data61), Zhi Zhang (The University of Western Australia), Shuo Wang (Shanghai Jiao Tong University), Rayne Holland (CSIRO's Data61), Anmin Fu (Nanjing University of Science and Technology), Minhui Xue (CSIRO's Data61), Derek Abbott (The University of Adelaide, Australia)

Read More

TZ-DATASHIELD: Automated Data Protection for Embedded Systems via Data-Flow-Based...

Zelun Kong (University of Texas at Dallas), Minkyung Park (University of Texas at Dallas), Le Guan (University of Georgia), Ning Zhang (Washington University in St. Louis), Chung Hwan Kim (University of Texas at Dallas)

Read More

Understanding Data Importance in Machine Learning Attacks: Does Valuable...

Rui Wen (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security)

Read More