Stop Hiding The Sharp Knives: The WebAssembly Linux Interface

• URL: http://arxiv.org/abs/2312.03858v1
• Date: Wed, 6 Dec 2023 19:11:15 GMT
• Title: Stop Hiding The Sharp Knives: The WebAssembly Linux Interface
• Authors: Arjun Ramesh, Tianshu Huang, Ben L. Titzer, Anthony Rowe
• Abstract summary: WebAssembly is a portable binary format targetable from many programming languages. WebAssembly lacks many standard system interfaces, making it difficult to reuse existing applications. This paper proposes WALI: The WebAssembly Linux Interface, a thin layer over Linux's userspace system calls.
• Score: 1.5439729828544784
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: WebAssembly is gaining popularity as a portable binary format targetable from many programming languages. With a well-specified low-level virtual instruction set, minimal memory footprint and many high-performance implementations, it has been successfully adopted for lightweight in-process memory sandboxing in many contexts. Despite these advantages, WebAssembly lacks many standard system interfaces, making it difficult to reuse existing applications. This paper proposes WALI: The WebAssembly Linux Interface, a thin layer over Linux's userspace system calls, creating a new class of virtualization where WebAssembly seamlessly interacts with native processes and the underlying operating system. By virtualizing the lowest level of userspace, WALI offers application portability with little effort and reuses existing compiler backends. With WebAssembly's control flow integrity guarantees, these modules gain an additional level of protection against remote code injection attacks. Furthermore, capability-based APIs can themselves be virtualized and implemented in terms of WALI, improving reuse and robustness through better layering. We present an implementation of WALI in a modern WebAssembly engine and evaluate its performance on a number of applications which we can now compile with mostly trivial effort.

Related papers

• Comparing Security and Efficiency of WebAssembly and Linux Containers in Kubernetes Cloud Computing [0.0]
  This study investigates the potential of WebAssembly as a more secure and efficient alternative to Linux containers for executing untrusted code in cloud computing with containers. Security analyses demonstrate that both Linux containers and WebAssembly have attack surfaces when executing untrusted code, but WebAssembly presents a reduced attack surface due to an additional layer of isolation.
  arXiv  Detail & Related papers  (2024-11-02T23:35:19Z)
• Cyber-physical WebAssembly: Secure Hardware Interfaces and Pluggable Drivers [3.3267678659285913]
  This work presents WASI proposals and proof-of-concept implementations to enable hardware interaction with I2C and USB. This is achieved by running the device drivers within WebAssembly as well. A thorough evaluation of the proof of concepts shows that WASI-USB introduces a minimal overhead of at most 8% compared to native operating system USB APIs.
  arXiv  Detail & Related papers  (2024-10-30T11:21:22Z)
• Securing Stack Smashing Protection in WebAssembly Applications [0.0]
  Previous work has shown that WebAssembly is vulnerable to buffer overflow due to the lack of effective protection mechanisms. We evaluate the implementation of Stack Smashing Protection (SSP) in WebAssembly standalone runtimes, and uncover two weaknesses in their current implementation.
  arXiv  Detail & Related papers  (2024-10-23T14:41:59Z)
• WebAssembly and Security: a review [0.8962460460173961]
  We analyze 121 papers by identifying seven different security categories. We aim to fill this gap by proposing a comprehensive review of research works dealing with security in WebAssembly.
  arXiv  Detail & Related papers  (2024-07-17T03:37:28Z)
• Flash-VStream: Memory-Based Real-Time Understanding for Long Video Streams [78.72965584414368]
  We present Flash-VStream, a video-language model that simulates the memory mechanism of human. Compared to existing models, Flash-VStream achieves significant reductions in latency inference and VRAM consumption. We propose VStream-QA, a novel question answering benchmark specifically designed for online video streaming understanding.
  arXiv  Detail & Related papers  (2024-06-12T11:07:55Z)
• StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation [2.1094456929188676]
  StackSight visualizes and tracks virtual stack alterations via a static analysis algorithm and then applies chain-of-thought prompting. Evaluation results show that StackSight significantly improves WebAssembly decompilation. Our user study also demonstrates that code snippets generated by StackSight have significantly higher win rates and enable a better grasp of code semantics.
  arXiv  Detail & Related papers  (2024-06-07T01:08:17Z)
• OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments [87.41051677852231]
  We introduce OSWorld, the first-of-its-kind scalable, real computer environment for multimodal agents. OSWorld can serve as a unified, integrated computer environment for assessing open-ended computer tasks. We create a benchmark of 369 computer tasks involving real web and desktop apps in open domains, OS file I/O, and spanning multiple applications.
  arXiv  Detail & Related papers  (2024-04-11T17:56:05Z)
• VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding? [115.60866817774641]
  Multimodal Large Language models (MLLMs) have shown promise in web-related tasks. evaluating their performance in the web domain remains a challenge due to the lack of comprehensive benchmarks. bench is a multimodal benchmark designed to assess the capabilities of MLLMs across a variety of web tasks.
  arXiv  Detail & Related papers  (2024-04-09T02:29:39Z)
• mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR using Program Synthesis [48.01697184432969]
  mlirSynth translates programs from lower-level MLIR dialects to high-level ones without manually defined rules. We demonstrate its effectiveness reviby raising C programs to two distinct high-level MLIR dialects, which enables us to use existing high-level dialect specific compilation flows.
  arXiv  Detail & Related papers  (2023-10-06T12:21:50Z)
• InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback [50.725076393314964]
  We introduce InterCode, a lightweight, flexible, and easy-to-use framework of interactive coding as a standard reinforcement learning environment. Our framework is language and platform agnostic, uses self-contained Docker environments to provide safe and reproducible execution. We demonstrate InterCode's viability as a testbed by evaluating multiple state-of-the-art LLMs configured with different prompting strategies.
  arXiv  Detail & Related papers  (2023-06-26T17:59:50Z)
• Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection [64.67495502772866]
  Large Language Models (LLMs) are increasingly being integrated into various applications. We show how attackers can override original instructions and employed controls using Prompt Injection attacks. We derive a comprehensive taxonomy from a computer security perspective to systematically investigate impacts and vulnerabilities.
  arXiv  Detail & Related papers  (2023-02-23T17:14:38Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.