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Proceedings of the ACM on Programming Languages
Article . 2019 . Peer-reviewed
License: CC BY
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Article . 2020
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DBLP
Article . 2020
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The high-level benefits of low-level sandboxing

Authors: Michael Sammler; Deepak Garg 0001; Derek Dreyer; Tadeusz Litak;

The high-level benefits of low-level sandboxing

Abstract

Sandboxing is a common technique that allows low-level, untrusted components to safely interact with trusted code. However, previous work has only investigated the low-level memory isolation guarantees of sandboxing, leaving open the question of the end-to-end guarantees that sandboxing affords programmers. In this paper, we fill this gap by showing that sandboxing enables reasoning about the known concept of robust safety , i.e. , safety of the trusted code even in the presence of arbitrary untrusted code. To do this, we first present an idealized operational semantics for a language that combines trusted code with untrusted code. Sandboxing is built into our semantics. Then, we prove that safety properties of the trusted code (as enforced through a rich type system) are upheld in the presence of arbitrary untrusted code, so long as all interactions with untrusted code occur at the “any” type (a type inhabited by all values). Finally, to alleviate the burden of having to interact with untrusted code at only the “any” type, we formalize and prove safe several wrappers , which automatically convert values between the “any” type and much richer types. All our results are mechanized in the Coq proof assistant.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    19
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
Green
Published in a Diamond OA journal