Prefix Siphoning: Exploiting LSM-Tree Range Filters For Information Disclosure (Full Version)

Adi Kafuman, Moshik Hershcovitch, Adam Morrison
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Abstract

Key-value stores typically leave access control to the systems for which they act as storage engines. Unfortunately, attackers may circumvent such read access controls via timing attacks on the key-value store, which use differences in query response times to glean information about stored data. To date, key-value store timing attacks have aimed to disclose stored values and have exploited external mechanisms that can be disabled for protection. In this paper, we point out that key disclosure is also a security threat -- and demonstrate key disclosure timing attacks that exploit mechanisms of the key-value store itself. We target LSM-tree based key-value stores utilizing range filters, which have been recently proposed to optimize LSM-tree range queries. We analyze the impact of the range filters SuRF and prefix Bloom filter on LSM-trees through a security lens, and show that they enable a key disclosure timing attack, which we call prefix siphoning. Prefix siphoning successfully leverages benign queries for non-present keys to identify prefixes of actual keys -- and in some cases, full keys -- in scenarios where brute force searching for keys (via exhaustive enumeration or random guesses) is infeasible.
前缀虹吸:利用lsm树范围过滤器进行信息披露(完整版)
键值存储通常将访问控制留给它们充当存储引擎的系统。不幸的是,攻击者可以通过对键值存储的定时攻击来规避这种读访问控制,这种攻击使用查询响应时间的差异来收集有关存储数据的信息。迄今为止,键值存储定时攻击的目标是泄露存储的值,并利用了可以禁用保护的外部机制。在本文中,我们指出密钥披露也是一种安全威胁,并演示了利用键值存储本身机制的密钥披露定时攻击。我们的目标是利用范围过滤器基于lsm树的键值存储,该过滤器最近被提出用于优化lsm树范围查询。我们通过安全镜头分析了范围过滤器SuRF和前缀Bloom过滤器对lsm树的影响,并表明它们可以实现密钥披露定时攻击,我们称之为前缀虹吸。前缀虹吸管成功地利用对不存在的键的良性查询来识别实际键的前缀——在某些情况下是完整的键——在暴力搜索键(通过穷举枚举或随机猜测)不可行的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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