Showing posts from 2018

A couple ideas that went nowhere

I suspect a lot of people in academia end up having a lot of ideas and projects that went nowhere for any number of reasons – maybe there were insurmountable technical challenges, maybe the right person to work on it never materialized, or maybe it just got crowded out by other projects and never picked back up. Here are a couple of mine. For each I'll try to indicate why it fell by the wayside, and whether I think it could be resurrected (if you're interested in doing some idea necromancy, let me know! :)). Detecting Flush+Flush Among the flurry of microarchitectural side channel attacks that eventually culminated in the devastating Spectre and Meltdown attacks was one that has received relatively little attention: Flush+Flush. The base of the attack is the observation that  clflush  takes a different amount of time depending on whether the address to be flushed was already in the cache or not. Gruss et al.  had a nice paper on this variant of the attack at DIMVA 2016

Of Bugs and Baselines

Summary : recently published results on the LAVA-M synthetic bug dataset are exciting. However, I show that much simpler techniques can also do startlingly well on this dataset; we need to be cautious in our evaluations and not rely too much on getting a high score on a single benchmark. A New Record The LAVA synthetic bug corpora have been available now for about a year and a half. I've been really excited to see new bug-finding approaches (particularly fuzzers) use the LAVA-M dataset as a benchmark, and to watch as performance on that dataset steadily improved. Here's how things have progressed over time. Performance on the LAVA-M dataset over time. Note that because the different utilities have differing numbers of bugs, this picture presents a slightly skewed view of how successful each approach was by normalizing the performance on each utility. Also, SBF was only evaluated on base64 (where it did very well), and Vuzzer's performance on md5sum is due to lar