UC Riverside

Memory analysis serves as a foundation for many security applications such as memory forensics, virtual machine introspection and malware investigation. However, malware, or more specifically a kernel rootkit, can often tamper with kernel memory data, putting the trustworthiness of memory analysis under question. With the rapid deployment of cloud computing and increase of cyber attacks, there is a pressing need to systematically study and understand the problem of memory analysis. In particular, without ground truth, the quality of the memory analysis tools widely used for analyzing closed-source operating systems (like Windows) has not been thoroughly studied. Moreover, while it is widely accepted that value manipulation attacks pose a threat to memory analysis, its severity has not been explored and well understood. To answer these questions, we have devised a number of novel analysis techniques including (1) binary level ground-truth collection, and (2) value equivalence set directed field mutation. Our experimental results demonstrate not only that the existing tools are inaccurate even under a non-malicious context, but also that value manipulation attacks are practical and severe. Finally, we show that exploiting information redundancy can be a viable direction to mitigate value manipulation attacks, but checking information equivalence alone is not an ultimate solution.