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EnclaveDom: Privilege Separation for Large-TCB Applications in Trusted Execution Environments (1907.13245v2)

Published 30 Jul 2019 in cs.CR and cs.OS

Abstract: Trusted executions environments (TEEs) such as Intel(R) SGX provide hardware-isolated execution areas in memory, called enclaves. By running only the most trusted application components in the enclave, TEEs enable developers to minimize the TCB of their applications thereby helping to protect sensitive application data. However, porting existing applications to TEEs often requires considerable refactoring efforts, as TEEs provide a restricted interface to standard OS features. To ease development efforts, TEE application developers often choose to run their unmodified application in a library OS container that provides a full in-enclave OS interface. Yet, this large-TCB development approach now leaves sensitive in-enclave data exposed to potential bugs or vulnerabilities in third-party code imported into the application. Importantly, because the TEE libOS and the application run in the same enclave address space, even the libOS management data structures (e.g. file descriptor table) may be vulnerable to attack, where in traditional OSes these data structures may be protected via privilege isolation. We present EnclaveDom, a privilege separation system for large-TCB TEE applications that partitions an enclave into tagged memory regions, and enforces per-region access rules at the granularity of individual in-enclave functions. EnclaveDom is implemented on Intel SGX using Memory Protection Keys (MPK) for memory tagging. To evaluate the security and performance impact of EnclaveDom, we integrated EnclaveDom with the Graphene-SGX library OS. While no product or component can be absolutely secure, our prototype helps protect internal libOS management data structures against tampering by application-level code. At every libOS system call, EnclaveDom then only grants access to those internal data structures which the syscall needs to perform its task.

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Authors (3)
  1. Marcela S. Melara (8 papers)
  2. Michael J. Freedman (8 papers)
  3. Mic Bowman (5 papers)
Citations (27)