Visible to the public Shredder: Breaking Exploits Through API Specialization

TitleShredder: Breaking Exploits Through API Specialization
Publication TypeConference Paper
Year of Publication2018
AuthorsMishra, Shachee, Polychronakis, Michalis
Conference NameProceedings of the 34th Annual Computer Security Applications Conference
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6569-7
KeywordsAPIs, compositionality, pubcrawl, resilience, Resiliency

Code reuse attacks have been a threat to software security since the introduction of non-executable memory protections. Despite significant advances in various types of additional defenses, such as control flow integrity (CFI) and leakage-resilient code randomization, recent code reuse attacks have demonstrated that these defenses are often not enough to prevent successful exploitation. Sophisticated exploits can reuse code comprising larger code fragments that conform to the enforced CFI policy and which are not affected by randomization. As a step towards improving our defenses against code reuse attacks, in this paper we present Shredder, a defense-in-depth exploit mitigation tool for the protection of closed-source applications. In a preprocessing phase, Shredder statically analyzes a given application to pinpoint the call sites of potentially useful (to attackers) system API functions, and uses backwards data flow analysis to derive their expected argument values and generate whitelisting policies in a best-effort way. At runtime, using library interposition, Shredder exposes to the protected application only specialized versions of these critical API functions, and blocks any invocation that violates the enforced policy. We have experimentally evaluated our prototype implementation for Windows programs using a large set of 251 shellcode and 30 code reuse samples, and show that it improves significantly upon code stripping, a state-of-the-art code surface reduction technique, by blocking a larger number of malicious payloads with negligible runtime overhead.

Citation Keymishra_shredder:_2018