The entropy factor

I have been dedicating my last few posts to the EntropyKey limitations and to shooting down Entropy Broker so I guess it is time for me to bring good news to my users, or at least some more usable news.

Let’s start with some positive news about EntropyKey; I have already suggested in the latter post that the problem I was getting with the key not working after a reboot could have been linked to the use of the userland USB access method. I can now confirm this: my router reboots fine with the CDC-based access. Unfortunately this brings up a different point: Linux’s CDC-ACM driver is far from perfect; as I pointed out, Simtec has a compatibility table for the kernel versions that are known to be defective. And even the latest release (2.6.38) is only partially fine — there are fixes in that relates to possible memory corruption and null pointer dereferences in the drivers. But it definitely makes the EntropyKey much more useful than it might have been suggested by my post there.

I also wanted to explain a bit better what I’m trying to look at with entropy, processes creation, and load. One of the two EntropyKey devices I own is connected to Yamato, which is the same box that runs the tinderbox. The entropy on Yamato tends to be quite low in general, and when I was using it as my main workstation, it was feeling sluggish — thus why I got the Key. I started monitoring it lately because I was noticing the Key not behaving properly, and beside the already noted issues with the userland access method, I have noticed a different pattern: when the load (and the running processes) spikes, the entropy fell for a while, without it being replenished in time. I’m still not sure if it’s simply the process creation eating away the entropy (for the ASLR mostly, since Yamato, unlike my router, doesn’t use SSP and thus doesn’t require canaries), or if the build process for ChromiumOS (which is what triggers those spikes) eats up the entropy by itself.

Thanks to upstream as I said before, I know there are somewhere around 4KiB of entropy gathered by the key per second, which means if something drains more than 4KiB/second, /dev/urandom will start re-using entropy. I have discarded the notion that it might have been a priority issue since I made sure to decrease the niceness of the ekeyd daemon, and it didn’t make any significant issue; on the other hand I’m now experimenting with using the same interface designed for vservers that Jaervosz helped getting into Gentoo. This method splits the process reading data from the key and that of sending it to the kernel — a quick check shows me that it does have better results, which would suggest that there are indeed performance-related problems, more than high-level of crypto consumption, at least on basic usage — I have yet to run a full rebuild of ChromiumOS in this configuration, since it’s over 6am and I’ll probably not sleep today.

Actually, moving to the split EGD server/client interface hopefully should also help me by providing more entropy for Raven (my frontend system) without using timer_entropyd, which has a nasty, completely load-linked dip in entropy generated when the load spikes. as Alex points out in the comments of the latter post, the quality of entropy also matters.

In parallel with the entropy issues in Yamato, I have entropy issues with my two vservers, one of which runs this blog, the other runs xine’s bugzilla — and both of which seem to have huge trouble with missing entropy, although in slightly different ways. The former, Vanguard, never reached 1KiB of entropy during the last four days when I monitored it, and its daily range is usually below 300 bytes. The latter, Midas, has a spike in entropy availability during the night, when maintenance tasks run (mostly Bugzilla’s); I’m not sure if it’s because Apache then throttles HTTPS access or something else, but otherwise it also has the same range of entropy.

Since both Vanguard and Midas have an average amount of accesses over HTTPS, it made sense to me to consider this lack of entropy as a problem. Unfortunately running timer_entropyd there is not an option: the virtualisation software used does not let me inject further entropy into the system, which is quite a pain in the lower back side. When I first inspected Entropy Broker, I was thrilled to read that OpenSSL supports accessing EGD sockets directly rather than through the kernel-exposed /dev/yrandom device, since the EGD sockets are handled entirely in userland, and thus wouldn’t hit the limitation of the virtualised envrionment. With Entropy Broker being.. broken, I was still able to track down an alternative to that: PRNGD a pseudo-random number generation daemon that works entirely in user-space by using a number of software sources to provide fast and decent random number sources.

OpenSSL, OpenSSH and other software explicitly provide support for accessing EGD sockets, and explicitly refer to PRNGD as an alternative to the OS-provided interfaces. Unfortunately, neither would work out of the box for Gentoo — the former will look into EGD sockets only if the /dev/urandom and /dev/random devices wouldn’t have enough data to provide enough random bytes as requested (which is never going to happen with /dev/urandom), and has to have its sources’ edited to actually have a chance to use EGD, even so it would (rightly) privilege the /dev/random device; OpenSSH instead requires for an extra parameter to be passed to the ./configure call. For those interested, the ekey-egd-linux package can inject this data back into the kernel, like Entropy Broker would have done if it worked.

A tentative ebuild for prngd is in my overlay but I’m not sure if and when I’ll add it to the main tree. First of all, I haven’t compared the entropy’s quality yet, and it might well be that the PRNGD method is going to give very bad results, but I’m also quite concerned about the sources’ license: it seems to be a mess of as-is, MIT and other licenses altogether. While Gentoo is not as strict as Debian in the license handling, it doesn’t sound like something I’d love to keep around with my name tagged on it.

Sigh, 7am, I’ll probably be awakened in two hours again. I really need to get myself some kind of vacation, somewhere I can spend time reading and/or listening to music all day long for a week. Sigh. I wish!

4 thoughts on “The entropy factor

  1. Have you looked at RNGd, part of sys-apps/rng-tools? It provides a generic method for injecting entropy into the kernel.Also worth a mention is pyved, from…. I’ve found it’s strangely faster than video_entropyd, although rather incomplete.


  2. I’m surprised that you haven’t mentioned sys-apps/haveged in your recent posts about entropy. I don’t know if it will help with your vserver issues, since I don’t have any vservers to test on, but haveged generates a staggering amount of entropy. I have not found a way to empty the entropy pool on my system with haveged running.As for the “quality” of the entropy it supplies: dieharder can’t seem to tell that it’s not a true random number generator when I run tests against /dev/random (and even that can’t empty the pool), and /dev/urandom’s scores improve with haveged. I’m pretty sure it’s “secure enough” for the average user.


  3. I discarded haveged because it segfaulted on me at the first try… not really suggesting confidence here. But, as far as I know, it also provides the same kind of kernel interface that I’m disallowed to use.


  4. I can confirm you that an entropy of 4KiB/s isn’t enough to serve a couple of very-low-traffic web sites with HTTPS , especially on a Gentoo Hardened host; the EntropyKey is quite useless in these scenarios.Time ago I have used some homemade HRNG to improve SSL encryption for our VPN server and the responsiveness of other internal servers:1- Arduino + HRNG provided 4MiB/s and worked great;2- Whirlygig [1] provided 1MiB/s and worked quite well;Whirlygig was the simplest solution but the provided entropy poll wasn’t enough to satisfy our VPN needs; in the end we used 1 Arduino board for the VPN traffic and several Whirlygig boards for all the other servers and we were able to sustain up to 5 concurrent very-high-traffic VPN connections without suffer slowness and congestion.All you need is a bigger randomness, try Whirlygig.[1]


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