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 ) )

THEMIS: Regulating Textual Inversion for Personalized Concept Censorship

Yutong Wu (Nanyang Technological University), Jie Zhang (Centre for Frontier AI Research, Agency for Science, Technology and Research (A*STAR), Singapore), Florian Kerschbaum (University of Waterloo), Tianwei Zhang (Nanyang Technological University)

Read More

Secure IP Address Allocation at Cloud Scale

Eric Pauley (University of Wisconsin–Madison), Kyle Domico (University of Wisconsin–Madison), Blaine Hoak (University of Wisconsin–Madison), Ryan Sheatsley (University of Wisconsin–Madison), Quinn Burke (University of Wisconsin–Madison), Yohan Beugin (University of Wisconsin–Madison), Engin Kirda (Northeastern University), Patrick McDaniel (University of Wisconsin–Madison)

Read More

Sheep's Clothing, Wolf's Data: Detecting Server-Induced Client Vulnerabilities in...

Fangming Gu (Institute of Information Engineering, Chinese Academy of Sciences), Qingli Guo (Institute of Information Engineering, Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology, Chinese Academy of Sciences), Qinghe Xie (Institute of Information Engineering, Chinese Academy of Sciences), Beibei Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Kangjie Lu (University of Minnesota),…

Read More

Rethink Custom Transformers for Binary Analysis

Heng Yin, Professor, Department of Computer Science and Engineering, University of California, Riverside

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)