Lost in the Pages: WebAssembly Code Recovery through SEV-SNP's Exposed Address Space

• URL: http://arxiv.org/abs/2512.14376v1
• Date: Tue, 16 Dec 2025 13:05:15 GMT
• Title: Lost in the Pages: WebAssembly Code Recovery through SEV-SNP's Exposed Address Space
• Abstract summary: We introduce a new Wasm code-confidentiality attack that exploits exposed address-space information in TEEs.<n>Our attack enables the extraction of crucial execution features which, when combined with additional side channels, allows us to with high reliability obtain more than 70% of the code.
• Score: 1.2891210250935148
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: WebAssembly (Wasm) has risen as a widely used technology to distribute computing workloads on different platforms. The platform independence offered through Wasm makes it an attractive solution for many different applications that can run on disparate infrastructures. In addition, Trusted Execution Environments (TEEs) are offered in many computing infrastructures, which allows also running security sensitive Wasm workloads independent of the specific platforms offered. However, recent work has shown that Wasm binaries are more sensitive to code confidentiality attacks than native binaries. The previous result was obtained for Intel SGX only. In this paper, we take this one step further, introducing a new Wasm code-confidentiality attack that exploits exposed address-space information in TEEs. Our attack enables the extraction of crucial execution features which, when combined with additional side channels, allows us to with high reliability obtain more than 70% of the code in most cases. This is a considerably larger amount than was previously obtained by single stepping Intel SGX where only upwards to 50% of the code could be obtained.

Related papers

• EnclaveX: End-to-End Confidential AI with CPU/GPU TEEs [0.26249027950824505]
  Large Language Models (LLMs) have rapidly proliferated, driving widespread adoption of AI applications.<n>Most deployments rely on centralized infrastructures such as Microsoft Azure, Google Cloud, or AWS, requiring users to share sensitive data and training or fine-tuning code.<n>This dependence raises significant security and privacy concerns, as cloud providers must be trusted to ensure confidentiality and integrity.<n>We propose mechanisms to ensure confidentiality and integrity at both the VM level (via Intel TDX and AMD SEV-SNP) and the application level, highlighting vulnerabilities such as administrators' ability to access confidential VM contents.
  arXiv  Detail & Related papers  (2026-06-30T09:35:28Z)
• ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks? [92.21756459993695]
  Exploitation is a challenging task because it requires low-level program reasoning.<n>Despite its importance and diagnostic value, exploitation remains under-evaluated.<n>We introduce ExploitGym, a large-scale, diverse, realistic benchmark on the exploitation capabilities of AI agents.
  arXiv  Detail & Related papers  (2026-05-11T18:00:14Z)
• Empirical Study of Code Large Language Models for Binary Security Patch Detection [12.110226735365643]
  Security patch detection (SPD) is crucial for maintaining software security, as unpatched vulnerabilities can lead to severe security risks.<n>In recent years, numerous learning-based SPD approaches have demonstrated promising results on source code.<n>However, these approaches cannot be applied to closed-source applications and proprietary systems that constitute a significant portion of real-world software.
  arXiv  Detail & Related papers  (2025-09-07T13:31:43Z)
• Decompiling Smart Contracts with a Large Language Model [51.49197239479266]
  Despite Etherscan's 78,047,845 smart contracts deployed on (as of May 26, 2025), a mere 767,520 ( 1%) are open source.<n>This opacity necessitates the automated semantic analysis of on-chain smart contract bytecode.<n>We introduce a pioneering decompilation pipeline that transforms bytecode into human-readable and semantically faithful Solidity code.
  arXiv  Detail & Related papers  (2025-06-24T13:42:59Z)
• VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents [74.6761188527948]
  Computer-Use Agents (CUAs) with full system access pose significant security and privacy risks.<n>We investigate Visual Prompt Injection (VPI) attacks, where malicious instructions are visually embedded within rendered user interfaces.<n>Our empirical study shows that current CUAs and BUAs can be deceived at rates of up to 51% and 100%, respectively, on certain platforms.
  arXiv  Detail & Related papers  (2025-06-03T05:21:50Z)
• Post-Quantum Cryptography: An Analysis of Code-Based and Lattice-Based Cryptosystems [55.49917140500002]
  Quantum computers will be able to break modern cryptographic systems using Shor's Algorithm.<n>We first examine the McEliece cryptosystem, a code-based scheme believed to be secure against quantum attacks.<n>We then explore NTRU, a lattice-based system grounded in the difficulty of solving the Shortest Vector Problem.
  arXiv  Detail & Related papers  (2025-05-06T03:42:38Z)
• SecScale: A Scalable and Secure Trusted Execution Environment for Servers [0.36868085124383626]
  Intel plans to deprecate its most trustworthy enclave, SGX, on its 11th and 12th generation processors. We propose SecScale that uses some new ideas centered around speculative execution. We show that we are 10% faster than the nearest competing alternative.
  arXiv  Detail & Related papers  (2024-07-18T15:14:36Z)
• Dynamic Frequency-Based Fingerprinting Attacks against Modern Sandbox Environments [7.753621963239778]
  We investigate the possibility of fingerprinting containers through CPU frequency reporting sensors in Intel and AMD CPUs. We demonstrate that Docker images exhibit a unique frequency signature, enabling the distinction of different containers with up to 84.5% accuracy. Our empirical results show that these attacks can also be carried out successfully against all of these sandboxes in less than 40 seconds.
  arXiv  Detail & Related papers  (2024-04-16T16:45:47Z)
• The Road to Trust: Building Enclaves within Confidential VMs [17.064775757967627]
  NestedSGX is a framework which leverages virtual machine privilege level (VMPL) It considers the guest OS untrusted for loading potentially malicious code. It ensures that only trusted and measured code executed within the enclave can be remotely attested.
  arXiv  Detail & Related papers  (2024-02-18T03:15:02Z)
• HasTEE+ : Confidential Cloud Computing and Analytics with Haskell [50.994023665559496]
  Confidential computing enables the protection of confidential code and data in a co-tenanted cloud deployment using specialized hardware isolation units called Trusted Execution Environments (TEEs) TEEs offer low-level C/C++-based toolchains that are susceptible to inherent memory safety vulnerabilities and lack language constructs to monitor explicit and implicit information-flow leaks. We address the above with HasTEE+, a domain-specific language (cla) embedded in Haskell that enables programming TEEs in a high-level language with strong type-safety.
  arXiv  Detail & Related papers  (2024-01-17T00:56:23Z)
• Empowering WebAssembly with Thin Kernel Interfaces [1.4133405185767076]
  This paper proposes thin kernel interfaces for Wasm, which directly expose OS userspace syscalls without breaking intra-process sandboxing.<n>Existing capability-based APIs for Wasm, such as WASI, can be implemented as a Wasm module over kernel interfaces.<n>We present an implementation of this concept for two kernels -- Linux and Zephyr -- by extending a modern Wasm engine.
  arXiv  Detail & Related papers  (2023-12-06T19:11:15Z)
• SOCI^+: An Enhanced Toolkit for Secure OutsourcedComputation on Integers [50.608828039206365]
  We propose SOCI+ which significantly improves the performance of SOCI. SOCI+ employs a novel (2, 2)-threshold Paillier cryptosystem with fast encryption and decryption as its cryptographic primitive. Compared with SOCI, our experimental evaluation shows that SOCI+ is up to 5.4 times more efficient in computation and 40% less in communication overhead.
  arXiv  Detail & Related papers  (2023-09-27T05:19:32Z)
• SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices [67.65883495888258]
  We present SyzTrust, the first state-aware fuzzing framework for vetting the security of resource-limited Trusted OSes. SyzTrust adopts a hardware-assisted framework to enable fuzzing Trusted OSes directly on IoT devices. We evaluate SyzTrust on Trusted OSes from three major vendors: Samsung, Tsinglink Cloud, and Ali Cloud.
  arXiv  Detail & Related papers  (2023-09-26T08:11:38Z)

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.