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SNAS: A Multi-Layer Defense-in-Depth Architecture for Secure Egress in Sandboxed Workloads

arXiv Security Archived Jun 17, 2026 ✓ Full text saved

arXiv:2606.17533v1 Announce Type: new Abstract: Snowpark enables data engineering and AI/ML workloads in Snowflake by executing user-defined functions in secure sandboxes. Many of these workloads require external connectivity to access cloud APIs, external databases, or feature stores, creating a dependability challenge: how to provide transparent network access while preserving strict multi-tenant isolation and resource fairness. This paper presents Secure Network Access in Snowpark (SNAS), a p

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    Computer Science > Cryptography and Security [Submitted on 16 Jun 2026] SNAS: A Multi-Layer Defense-in-Depth Architecture for Secure Egress in Sandboxed Workloads Niranjan Kumar Sharma, S Muralidhar, Samy Boshra-Riad, Mike Halcrow, Yuxiong He, Nitya Kumar Sharma, Shawn Xia, Haowei Yu, Elliott Brossard, Derek Denny-Brown, Choden Konigsmark, Bhanu Prakash, Brandon Baker, Andong Zhan Snowpark enables data engineering and AI/ML workloads in Snowflake by executing user-defined functions in secure sandboxes. Many of these workloads require external connectivity to access cloud APIs, external databases, or feature stores, creating a dependability challenge: how to provide transparent network access while preserving strict multi-tenant isolation and resource fairness. This paper presents Secure Network Access in Snowpark (SNAS), a production architecture for secure external communication from sandboxed workloads. SNAS combines Extended Berkeley Packet Filter (eBPF) packet filtering, Generic Network Virtualization Encapsulation (GENEVE) overlay networks, and distributed egress proxies for policy-driven egress control with low overhead. We describe the design, deployment, and measured production behavior of SNAS, including an eBPF-based bandwidth limiter using the Earliest Departure Time (EDT) algorithm, dual-tier policy enforcement, and safeguards for connection limiting and port exhaustion. SNAS is deployed across all Snowflake regions and supports large-scale production workloads including petabyte-scale data transfer and latency-sensitive external integrations. Comments: 10 pages, 7 figures. Accepted at the 53rd IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2026), June 23-26, 2026 Subjects: Cryptography and Security (cs.CR) ACM classes: C.2.0; C.2.6; D.4.6 Cite as: arXiv:2606.17533 [cs.CR]   (or arXiv:2606.17533v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.17533 Focus to learn more Submission history From: Niranjan Kumar Sharma [view email] [v1] Tue, 16 Jun 2026 05:19:59 UTC (1,298 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 17, 2026
    Archived
    Jun 17, 2026
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