Wednesday, November 18, 2009

ArcSight Logger VS Splunk

You are here because you are searching for information on Splunk vs. ArcSight Logger. I actually wrote this post months before posting it, but sat on it for reasons that may become apparent as you read on.

If you want to hear me talk about my experience with Logger 4.0 through the beta process and beyond, you can check out the video case study I did for ArcSight. In short, Logger is good at what it does, and Logger 4.0 is fast. Ridiculously fast.

But that's not what I want to talk about. I want to talk about the question that's on everyone's mind: ArcSight Logger vs. Splunk?

Comparing features, there's not a strong advantage in either camp. Everybody's got built-in collection based on file and syslog. Everybody's got a web interface with pretty graphs. The main way Logger excels here is in its ability to natively front-end data aggregation for ArcSight's ESM SIEM product. But if you've already got ESM, you're going to buy Logger anyway. So that leaves price and performance as the remaining differentiators.

Splunk can compete on price, especially for more specialized use cases where Logger needs the ArcSight Connector software to pick up data (i.e. Windows EventLog via WMI, or database rows via JDBC). And if you don't care about performance, implying that your needs are modest, Splunk may be cheaper for you for even the straightforward use cases because of the different licensing model that scales downward. So for smaller businesses, Splunk scales down.

For larger businesses, Logger scales up. For example, if you need to add storage capacity to your existing Logger install, and you didn't buy the SAN-attached model, you just buy another Logger appliance. You then 'peer' the Logger appliances, split or migrate log flows, and continue to run search & reporting out of the same appliance you've been using, across all peer data stores. With Splunk? You buy and implement more hardware on your own. And pay for more licenses.

My thinking on performance? Logger 4.0 is a Splunk killer, plain and simple. To analogize using cars, Splunk is a Ford Taurus for log search. It gets you down the road, it's reliable, you can pick the entry model up cheap, and by now you know what you're getting. Logger 4.0, however, is a Zonda F with a Volvo price tag.

To bring the comparison to a fine point, I'd like to share a little story with you. It's kind of gossipy, but that makes it fun.

When ArcSight debuted Logger 4.0 and announced its GA release at their Protect conference last fall, they did a live shoot-out of a Logger 7200 running 4.0 with a vanilla install of Splunk 4 on comparable hardware and the same Linux distro (CentOS) that Logger is based on. They performed a simple keyword search in Splunk across 2 million events, which took just over 12 minutes to complete. That's not awful. But that same search against the same data set ran in about 3 seconds on Logger 4.

This would be an interesting end to an otherwise pretty boring story if it weren't for what happened next. Vendors other than ArcSight - partners, integrators, consultants, etc. - participate in their conference both as speakers and on the partner floor. One of these vendors, an integrator of both ArcSight and Splunk products, privately called ArcSight out for the demo. His theory was that a properly-tuned Splunk install would perform much better. Now, it's a little nuts (and perhaps a little more dangerous) to be an invited vendor at a conference and accuse the conference organizer of cooking a demo. But what happened next is even crazier. ArcSight wheeled the gear up to this guy's room and told him that if he could produce a better result during the conference that they would make an announcement to that effect.

Not one to shy away from a technical challenge, this 15-year infosec veteran skipped meals, free beer, presentations, more free beer, and a lot of sleep to tweak the Splunk box to get better performance out of it. That's dedication. There's no doubt in my mind that he wanted to win. Badly. I heard from him personally at the close of the conference that not only did he not make significant headway, but that all of his results were worse than the original 12 minute search time.

You weren't there, you're just reading about it on some dude's blog, so the impact isn't the same. But that was all the convincing I needed.

But if you need more convincing; we stuffed 6mos of raw syslog from various flavors of UNIX and Linux (3TB) into Logger 4 during the beta. I could keyword search the entire data set in 14 seconds. Regex searches were significantly worse. They took 32 seconds.

Monday, November 9, 2009

Reversing JavaScript Shellcode: A Step By Step How-To

With more and more exploits being written in JavaScript, even some 0-day, there is a need to be able to reverse exploits written in JavaScript beyond de-obfuscation. I spent some time this weekend searching Google for a simple way to reverse JavaScript shellcode to assembly. I know people do it all the time. It's hardly rocket science. Yet, I didn't find any good walk-throughs on how to do this. So I thought I'd write one.

For this walk-through, I'll start with JavaScript that has already been extracted from a PDF file and de-obfuscated. So this isn't step 1 of fully reversing a PDF exploit, but for the first several steps, check out Part 2 of this slide deck.

What you'll need:
  1. A safe place to play with exploits (I'll be using an image in VMWare Workstation.)
  2. JavaScript debugger (I highly recommend and will be using Didier Stevens' modified SpiderMonkey.)
  3. Perl
  4. The script, which you'll find further down in this post
  5. A C compiler and your favorite binary debugger

I'll be using one of the example Adobe Acrobat exploits from the aforementioned slides for this example. You can grab it from milw0rm.

Step 1 - Converting from UTF-encoded characters to ASCII
Most JavaScript shellcode is encoded as either UTF-8 or UTF-16 characters. It would be easy enough to write a tool to convert from any one of these formats to the typical \x-ed UTF-8 format that we're used to seeing shellcode in. But because of the diversity of encoding and obfuscation showing up in JavaScript exploits today, it's more reliable to use JavaScript to decode the shellcode.

For this task, you need a JavaScript debugger. Didier Stevens' SpiderMonkey mod is a great choice. Start by preparing the shellcode text for passing to the debugger. In this case, drop the rest of the exploit, and then wrap the unescape function in an eval function:

Now run this code through SpiderMonkey. SpiderMonkey will create two log files for the eval command, the one with our ASCII shellcode is eval.001.log.

Step 2 -
This is why I wrote this script, to take an ASCII dump of some shellcode and automate making it debugger-friendly.


# crap2shellcode - 11/9/2009 Paul Melson
# This script takes stdin from some ascii dump of shellcode
# (i.e. unescape-ed JavaScript sploit) and converts it to
# hex and outputs it in a simple C source file for debugging.
# gcc -g3 -o dummy dummy.c
# gdb ./dummy
# (gdb) display /50i shellcode
# (gdb) break main
# (gdb) run

use strict;
use warnings;

my $crap;
while($crap=<stdin>) {
my $hex = unpack('H*', "$crap");

my $len = length($hex);
my $start = 0;

print "#include <stdio.h>\n\n";
print "static char shellcode[] = \"";

for (my $i = 0; $i < length $hex; $i+=4) {
my $a = substr $hex, $i, 2;
my $b = substr $hex, $i+2, 2;
print "\\x$b\\x$a";
print "\";\n\n";

print "int main(int argc, char *argv[])\n";
print "{\n";
print " void (*code)() = (void *)shellcode;\n";
print " code();\n";
print " exit(0);\n";
print "}\n";
print "\n";


The output of passing eval.001.log through is a C program that makes debugging the shellcode easy.

Step 3 - View the shellcode/assembly in a debugger
First we have to build it. Since we know that this shellcode is a Linux bindshell the logical choice for where and how to build is Linux with gcc. Similarly, we can use gdb to dump the shellcode. For Win32 shellcode, we would probably pick Visual Studio Express and OllyDbg. Just about any Windows C compiler and debugger will work fine, though.

To build the C code we generated in step 2 with gcc, use the following:

gcc -g3 shellcode.c -o shellcode

The '-g3' flag builds the binary with labels for function stack tracing. This is necessary for debugging the binary. Or at least it makes it a whole lot easier.

Now open the binary in gdb, print *shellcode in x/50i format, set a breakpoint at main(), and run it.

$ gdb ./shellcode
(gdb) display /50i shellcode

(gdb) break main

(gdb) run