ReCon: Efficient Detection, Management, and Use of Non-Speculative Information Leakage

In a speculative side-channel attack, a secret is improperly accessed and then leaked by passing it to a transmitter instruction. Several proposed defenses effectively close this security hole by either delaying the secret from being loaded or propagated, or by delaying dependent transmitters (e.g., loads) from executing when fed with tainted input derived from an earlier speculative load. This results in a loss of memory-level parallelism and performance. A security definition proposed recently, in which data already leaked in non-speculative execution need not be considered secret during speculative execution, can provide a solution to the loss of performance. However, detecting and tracking non-speculative leakage carries its own cost, increasing complexity. The key insight of our work that enables us to exploit non-speculative leakage as an optimization to other secure speculation schemes is that the majority of non-speculative leakage is simply due to pointer dereferencing (or base-address indexing) - essentially what many secure speculation schemes prevent from taking place speculatively. We present ReCon that: i) efficiently detects non-speculative leakage by limiting detection to pairs of directly-dependent loads that dereference pointers (or index a base-address); and ii) piggybacks non-speculative leakage information on the coherence protocol. In ReCon, the coherence protocol remembers and propagates the knowledge of what has leaked and therefore what is safe to dereference under speculation. To demonstrate the effectiveness of ReCon, we show how two state-of-the-art secure speculation schemes, Non-speculative Data Access (NDA) and speculative Taint Tracking (STT), leverage this information to enable more memorylevel parallelism both in a single core scenario and in a multicore scenario: NDA with ReCon reduces the performance loss by 28.7% for SPEC2017, 31.5% for SPEC2006, and 46.7% for PARSEC; STT with ReCon reduces the loss by 45.1%, 39%, and 78.6%, respectively.