构建可移植的深嵌套隐式信息流跟踪

L. S. D. Araújo, L. A. J. Marzulo, Tiago A. O. Alves, F. França, I. Koren, S. Kundu
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引用次数: 0

摘要

动态信息流跟踪已成功地用于防止各种攻击和检测对敏感信息的非法访问。大多数建议的解决方案只跟踪通过数据依赖关系传播污染的显式信息流。然而,最近的逃避攻击利用隐式流(在应用程序中使用控制流)来操纵数据,从而使恶意活动无法检测到。我们提出了NIFT——一个嵌套的隐式流跟踪机制,它将显式传播扩展到受控制依赖关系影响的指令。我们的技术在编译时生成污染指令,这些指令由专门的硬件执行,即使在深嵌套分支的情况下也可以隐式传播污染。此外,我们建议对在条件分支中执行的数据进行限制的污染传播,仅影响立即指令,而不是分支范围内的所有指令。我们的技术可以有效地定位隐式流并以微不足道的性能开销解决它们。此外,它还缓解了过度污染的问题。
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Building a portable deeply-nested implicit information flow tracking
Dynamic Information Flow Tracking has been successfully used to prevent a wide range of attacks and detect illegal access to sensitive information. Most proposed solutions only track the explicit information flow where the taint is propagated through data dependencies. However, recent evasion attacks exploit implicit flows, that use control flow in the application, to manipulate the data thus making the malicious activity undetectable. We propose NIFT - a nested implicit flow tracking mechanism that extends explicit propagation to instructions affected by a control dependency. Our technique generates taint instructions at compile time which are executed by specialized hardware to propagate taint implicitly even in cases of deeply-nested branches. In addition, we propose a restricted taint propagation for data executed in conditional branches that affects only immediate instructions instead of all instructions inside the branch scope. Our technique efficiently locates implicit flows and resolves them with negligible performance overhead. Moreover, it mitigates the over-tainting problem.
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