Internet-of-Things devices such as autonomous vehicular sensors, medical devices, and industrial cyber-physical systems commonly rely on small, resource-constrained microcontrollers (MCUs). MCU software is typically written in C and is prone to memory safety vulnerabilities that are exploitable by remote attackers to launch code reuse attacks and code/control data leakage attacks. We present Randezvous, a highly performant diversification-based mitigation to such attacks and their brute force variants on ARM MCUs. Atop code/data layout randomization and an efficient execute-only code approach, Randezvous creates decoy pointers to camouflage control data in memory; code pointers in the stack are then protected by a diversified shadow stack, local-to-global variable promotion, and return address nullification. Moreover, Randezvous adds a novel delayed reboot mechanism to slow down persistent attacks and mitigates control data spraying attacks via global guards. We demonstrate Randezvous’s security by statistically modeling leakage-equipped brute force attacks under Randezvous, crafting a proof-of-concept exploit that shows Randezvous’s efficacy, and studying a real-world CVE. Our evaluation of Randezvous shows low overhead on three benchmark suites and two applications.
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Block Oriented Programming: Automating Data-Only Attacks
With the widespread deployment of Control-Flow Integrity (CFI), control-flow hijacking attacks, and consequently code reuse attacks, are significantly more difficult. CFI limits control flow to well-known locations, severely restricting arbitrary code execution. Assessing the remaining attack surface of an application under advanced control-flow hijack defenses such as CFI and shadow stacks remains an open problem.
We introduce BOPC, a mechanism to automatically assess whether an attacker can execute arbitrary code on a binary hardened with CFI/shadow stack defenses. BOPC computes exploits for a target program from payload specifications written in a Turing-complete, high-level language called SPL that abstracts away architecture and program-specific details. SPL payloads are compiled into a program trace that executes the desired behavior on top of the target binary. The input for BOPC is an SPL payload, a starting point (e.g., from a fuzzer crash) and an arbitrary memory write primitive that allows application state corruption. To map SPL payloads to a program trace, BOPC introduces Block Oriented Programming (BOP), a new code reuse technique that utilizes entire basic blocks as gadgets along valid execution paths in the program, i.e., without violating CFI or shadow stack policies. We find that the problem of mapping payloads to program traces is NP-hard, so BOPC first reduces the search space by pruning infeasible paths and then uses heuristics to guide the search to probable paths. BOPC encodes the BOP payload as a set of memory writes.
We execute 13 SPL payloads applied to 10 popular applications. BOPC successfully finds payloads and complex execution traces ś which would likely not have been found through manual analysis ś while following the target’s Control-Flow Graph under an ideal CFI policy in 81% of the cases.
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- Award ID(s):
- 1801534
- NSF-PAR ID:
- 10095765
- Date Published:
- Journal Name:
- 25th ACM Conference on Computer and Communications Security (ACM CCS)
- Page Range / eLocation ID:
- 1868 to 1882
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3243734.3243739
