Today, a day after 1.3.2, we’ve released 1.4beta2. While 1.3.2 is an important update for those running 1.3.1 or lower, today’s release is where things get exciting. A lot of things were improved and added. Let me show some numbers first.
The 1.4beta2 release is a pretty big update over 1.4beta1 as it touches over 5k lines of code:
234 files changed, 5033 insertions(+), 3759 deletions(-)
Compared to 1.4beta2 vs yesterday’s 1.3.2 it’s clear over 11k lines of code are touched:
262 files changed, 11406 insertions(+), 5794 deletions(-)
Personally, I’ve been working on two main area’s: defrag engine and the luajit integration, and a couple of other things.
The defrag engine was the last major subsystem that still used a Big Lock. Defrag uses so called “trackers” to track fragments belonging to a single IP packet. These trackers are stored in a hash table. 1.3 and prior used a hash that had no locking, so it relied on a Big Lock to protect it’s operations. Suricata has had fine grained hashes for flow and host tables for some time already, so it made sense to port defrag over as well.
I’ve written about the luajit a couple of times already. While the basic functionality debuted in beta1, the code has been completely overhauled. The most important change that is user visible is the integration with the various HTTP inspection engines. This did result in a limitation though, for now you can just inspect one HTTP buffer per script.
A weird challenge with luajit is that it’s “state” needs to be in the 32 bit part of memory. The reason isn’t clear to me, but this gave us some trouble. Some users use many rules and agressive pattern matcher settings. When after this memory usage the luajit states had to be alloc’d, it failed. I’ve worked around this by allocating a bunch of states in advance, hoping they’ll end up in the proper memory. We’ll see how that will work.
I’ve also largely rewritten the optional rule profiling to perform better. Here too, a Big Lock was removed. The accounting is now first done on a per thread basis, and only merged at detection engine shut down. Another nice feature is that it will now print the profiling stats during a live rule reload as well.
Next, I’ve improved performance of the decode, stream and app layer event keywords. They were quite expensive as they were checked quite often. I’ve now added a prefilter check to the detection engine’s prefilter stage. Helps quite a bit!
So all in all quite a bit of changes. Please help us test this so we can move to a stable and high performing 1.4! 🙂