基于数据流跟踪的基址识别注入攻击检测

S. Katsunuma, H. Kurita, Ryota Shioya, Kazuto Shimizu, H. Irie, M. Goshima, S. Sakai
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引用次数: 15

摘要

部分程序存在缓冲区溢出等漏洞,容易受到地址注入攻击。之前提出的输入数据跟踪方法可以防止I-data(从输入数据派生的数据)被用作地址。但是,地址注入攻击的判定规则比较模糊,导致检测结果出现了很多假阳性和假阴性。通常,用作地址的数据由基址和地址偏移量组成。我们提出了一种架构技术来防止i数据覆盖b数据,b数据是本文中用作基址的数据。它动态地识别i数据和b数据。如果使用非b数据的i数据作为地址,则检测到地址注入。我们在基于pentium的Bochs仿真器上实现了该技术,并研究了其检测能力。我们认为该技术是目前提出的最精确的注射检测技术
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Base Address Recognition with Data Flow Tracking for Injection Attack Detection
Vulnerabilities such as buffer overflows exist in some programs, and such vulnerabilities are susceptible to address injection attacks. The input data tracking method, which was proposed before, prevents I-data, which are the data derived from the input data, being used as addresses. However, the rules to determine address injection attacks are vague, which produces many false-positives and false-negatives in detection results. Generally, the data used as an address consist of a base address and an address offset. We propose an architectural technique to prevent I-data overwriting B-data, which are the data used as base addresses in this paper. It dynamically recognizes the I-data and the B-data. Address injection is detected if I-data that are not B-data are used as addresses. We implemented the proposed technique on a Pentium-based Bochs emulator and investigated its detection capability. We believe that the technique is the most accurate injection detection technique proposed thus far
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