I got an interesting question recently:
Assuming a password is not in a dictionary, what length is required to make a brute force attack infeasible?
That’s a pretty good question, and we should be able to answer it fairly easily given a few assumptions.
The short answer is, using RNCryptor and some reasonable security assumptions, it would be very difficult to bruteforce an 8 character password randomly taken from all the easily typable characters on an English keyboard. The rest of this article will discuss my assumptions, and how you would calculate good lengths for other assumptions.
To work this out, we really just need to know three things:
 How many passwords exist for a given length?
 How much effort (resources x time) does it take to test a password?
 How much attacker effort is “feasible?”
How many passwords exist for a given length?
The number of passwords for a given length depends on the number of different characters we allow in a password. On common English keyboards, you can easily type 26 lowercase, 26 uppercase, 10 numbers, about 32 symbols, and space. That’s 95 different characters.^{1}
The number of passwords for a given set size (S) and a specific password length (n) is S^{n}.
What’s interesting about this function is how it reacts to changes in S and n. For example, let’s consider a fixed password size (n = 8), with a variable set size from S = 26 (lowercase English letters) to S = 3000 (roughly the number of everyday Chinese characters). Would we rather a long lowercase English password or a short Chinese password?^{2}
In this graph, we start at the same point (6 characters chosen from a set of 26). We then vary the length one character at a time (linearly) versus the set size by orders of magnitude (exponetially). Increasing the length of the password by two or three characters is better than increasing the number of available characters 10fold. So, given a choice, you’d rather have a long, random password than anything else. This is the principle of AES key sizes. Each bit is chosen from a set of just 2 “letters,” but 256 bits still provides a huge keyspace.
How much effort (resources x time) does it take to test a password?
By design, most of the time required to test a password in RNCryptor is spent converting the password into a key using PBKDF2. PBKDF2 is is designed to be slow specifically to make brute forcing difficult. RNCryptor uses 10,000 iterations to convert the password into a key. How long that takes to calculate depends on your machine, so we need to define some unit that we will measure our attack in. Since I happen to have one in front of me, we’re going to use “one core of an Early 2011 MacBook Pro” as the unit.
There are a couple of things to keep in mind when choosing this unit. First, you need to think in terms of what hardware your attacker is going to use against you, not the hardware you used to encrypt. So think at least in terms of desktops and servers, not iPhones. Second, remember that the proper unit is a “core,” not a system. PBKDF2 can’t be computed in parallel, but the attacker can easily spread many different PKBDF2 computations over as many cores as available. That said, it doesn’t really matter what the unit is; we just need a way to describe attacker resources.
How long does it take one unit to test one password? With the current version of the RNCryptor data format, it’s dependent on the length of the ciphertext. But the v4 data format will remove this overhead, so we’ll assume almost all the time is in the PBKDF2 iterations.
We could write a function to time this by hand, but Common Crypto provides
CCCalibratePBKDF()
to help us out. It will tell us how many rounds we need to achieve a certain
delay.^{3}
1 2 3 4 5 6 

This returns between 9,00010,000 on my machine. To keep things simple, we’ll say that one “unit” can calculate 10,000 PBKDF2 rounds (one RNCryptor password) in 10ms. Or alternatively, one unit can test approximately 100 passwords per second.
How much attacker effort is “feasible?”
Maybe by “feasible” we mean “in a few days on a laptop.” Or maybe by “feasible” we mean “within 100,000 coreyears (10 years on 10,000 cores, or a month on one million cores).” That isn’t as shocking a scale as you might think. Some secrets really do need to stay secret for decades, and 10,000 cores is small for a botnet, several of which have several million active hosts with multiple cores at any give time. You also have to consider technological advances. If the secret you encrypt today is being attacked ten years from now, you have to scale against those machines, not today’s machines.
Eventually you have to decide on some number. For general purposes, I like to use 100,000 coreyears (with my “Early 2011 MacBook Pro” being the equivalent of 8 “cores”). If your secret has a fairly short shelflife, you may be wiling to go as low as 1,000 coreyears, or for very sensitive information that needs protection for decades, you may want to scale to 10 million coreyears.
Putting it all together
To recap our assumptions:
 95 character set for passwords (S)
 100 password tests per coresecond, based on 10,000 PBKDF2 iterations (rate)
 100,000 coreyears of effort = 100,000 x (3 x 10^{7}) coreseconds (effort)
Now it’s just some fancy math^{4} to solve for length (which must be integral):
$$\newcommand{\unit}[1]{\mathrm{#1}}$$ $$rate = \frac{S^{length}}{effort}$$
$$S^{length} = rate \times effort$$
$$length = \left\lceil\log _S (rate \times effort)\right\rceil$$
$$length = \left\lceil\frac{\log(rate \times effort)}{\log(S)}\right\rceil$$
$$length = \left\lceil\frac{\log(100 \times (100,000 \times 3 \times 10^{7}))}{\log(95)}\right\rceil$$
$$length = 8$$
The careful reader may be asking “shouldn’t the attacker expect to find the password in half this time?” You’re completely correct. Since the correct password is as likely to be in the first half searched as the last half, the expected time is technically half as long. But it doesn’t matter. Because password length grows logithmically, halving or doubling the effort has little impact. You’ll still get 8 characters.
To get up to 10 million coreyears (two more orders of magnitude), just pushes us up to 9 characters. That shouldn’t be surprising, since there are almost 100 characters in our set, every time we add another character to the password we should expect to add two orders of magnitude to the difficulty.
What if the password were still random, but only selected from lowercase letters and numbers? Then we need 10 characters to get 100,000 coreyears of effort. So smaller character spaces increase the password length needs, but not by a lot.
What are the takeaways?
Between 8 and 10 random characters is a quite good password. Even with a much smaller number of iterations of PBKDF2, 10 character random passwords hold up well.
This analysis only applies when the attacker is bruteforcing the password space. Most attackers do not do it this way. They more often attack poorly chosen or reused passwords.
PBKDF2 is critical for slowing down bruteforce attacks. PBKDF2 adds several orders of magntiude to the attacker’s effort.
When thinking about spaces, orders of magnitude are more important than actual values. If you’re not adding an extra zero, you’re not making much impact. Try to have at least a couple of orders of magnitude safety margin against the resources you think the attacker will ever have over your time horizon.

I’m not including the tab key because it is very often not allowed in passwords, especially on the web.↩

When discussing “characters” here, I mean actual characters. It doesn’t matter how many bytes are used to represent them. So XX and 谢谢 are the same length for these purposes, no matter how they’re encoded.↩

While
CCCalibratePBKDF
accepts a password length, the results are not very sensitive (if at all) to its value. The most important parameter is the delay.↩ 
Not actually fancy math.↩