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

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 118 ) ) ) [post__not_in] => Array ( [0] => 20179 ) )

WIP: Towards Privacy Compliance by Design in the Matter...

Yichen Liu (Indiana University Bloomington), Jingwen Yan (Clemson University), Song Liao (Texas Tech University), Long Cheng (Clemson University), Luyi Xing (Indiana University Bloomington)

Read More

Density Boosts Everything: A One-stop Strategy for Improving Performance,...

Jianwen Tian (Academy of Military Sciences), Wei Kong (Zhejiang Sci-Tech University), Debin Gao (Singapore Management University), Tong Wang (Academy of Military Sciences), Taotao Gu (Academy of Military Sciences), Kefan Qiu (Beijing Institute of Technology), Zhi Wang (Nankai University), Xiaohui Kuang (Academy of Military Sciences)

Read More

EvoCrawl: Exploring Web Application Code and State using Evolutionary...

Xiangyu Guo (University of Toronto), Akshay Kawlay (University of Toronto), Eric Liu (University of Toronto), David Lie (University of Toronto)

Read More

SCAMMAGNIFIER: Piercing the Veil of Fraudulent Shopping Website Campaigns

Marzieh Bitaab (Arizona State University), Alireza Karimi (Arizona State University), Zhuoer Lyu (Arizona State University), Adam Oest (Amazon), Dhruv Kuchhal (Amazon), Muhammad Saad (X Corp.), Gail-Joon Ahn (Arizona State University), Ruoyu Wang (Arizona State University), Tiffany Bao (Arizona State University), Yan Shoshitaishvili (Arizona State University), Adam Doupé (Arizona State University)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)