(2019) RIDL: Rogue In-flight Data Load.
Abstract
We present Rogue In-flight Data Load (RIDL)1 , a new class of unprivileged speculative execution attacks to leak arbitrary data across address spaces and privilege boundaries (e.g., process, kernel, SGX, and even CPU-internal operations). Our reverse engineering efforts show such vulnerabilities originate from a variety of micro-optimizations pervasive in commodity (Intel) processors, which cause the CPU to speculatively serve loads using extraneous CPU-internal in-flight data (e.g., in the line fill buffers). Contrary to other state-of-the-art speculative execution attacks, such as Spectre, Meltdown and Foreshadow, RIDL can leak this arbitrary in-flight data with no assumptions on the state of the caches or translation data structures controlled by privileged software. The implications are worrisome. First, RIDL attacks can be implemented even from linear execution with no invalid page faults, eliminating the need for exception suppression mechanisms and enabling system-wide attacks from arbitrary unprivileged code (including JavaScript in the browser). To exemplify such attacks, we build a number of practical exploits that leak sensitive information from victim processes, virtual machines, kernel, SGX and CPU-internal components. Second, and perhaps more importantly, RIDL bypasses all existing “spot” mitigations in software (e.g., KPTI, PTE inversion) and hardware (e.g., speculative store bypass disable) and cannot easily be mitigated even by more heavyweight defenses (e.g., L1D flushing or disabling SMT). RIDL questions the sustainability of a per-variant, spot mitigation strategy and suggests more fundamental mitigations are needed to contain everemerging speculative execution attacks.
| Item Type: | Conference or Workshop Item (A Paper) (Paper) |
|---|---|
| Divisions: | Christian Rossow (System Security Group, SysSec) |
| Conference: | SP IEEE Symposium on Security and Privacy |
| Depositing User: | Giorgi Maisuradze |
| Date Deposited: | 23 Jun 2019 18:38 |
| Last Modified: | 24 Oct 2020 16:39 |
| Primary Research Area: | NRA3: Threat Detection and Defenses |
| URI: | https://publications.cispa.saarland/id/eprint/2921 |
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