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Memory corruption attacks remain the primary threat for computer security.Information flow tracking or taint analysis has been proven to be effectiveagainst most memory corruption attacks. However, there are two shortcomingswith current taint analysis based techniques. First, these techniques causeapplication slowdown by about 76% thereby limiting their practicality. Second,these techniques cannot handle non-control data attacks i.e., attacks that donot overwrite control data such as return address, but instead overwritecritical application configuration data or user identity data. In this work, toaddress these problems, we describe a coarse-grained taint analysis techniquethat uses information flow tracking at the level of application data objects.We propagate a one-bit taint over each application object that is modified byuntrusted data thereby reducing the taint management overhead considerably. Weperformed extensive experimental evaluation of our approach and show that itcan detect all critical attacks such as buffer overflows, and format stringattacks, including non-control data attacks. Unlike the currently knownapproaches that can detect such a wide range of attacks, our approach does notrequire the source code or any hardware extensions. Run-time performanceoverhead evaluation shows that, on an average, our approach causes applicationslowdown by only 37% which is an order of magnitude improvement over existingapproaches. Finally, since our approach performs run-time binaryinstrumentation, it is easier to integrate it with existing applications andsystems.

Coarse-grained Dynamic Taint Analysis for Defeating Control and Non-control Data Attacks