This is an archive of the original posts Andrew Roos made in 1995 to announce his discovery of weak keys in RC4. Even though most Wireless LAN access points avoid these keys since many years, this discovery eventually led to abandoning RC4 for use in WEP (“Wired Equivalent Privacy”) for Wi-Fi networks, as the privacy was no longer anywhere near wire-equivalent. The second part of his research is in the next post.

**From:** andrewr@vironix.co.za (Andrew Roos)**
Newsgroups:** sci.crypt

**Weak Keys in RC4**

Subject:

Subject:

**22 Sep 1995 09:59:45 GMT**

Date:

Date:

**Vironix**

Organization:

Organization:

**303**

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**<43u1eh$1j3@hermes.is.co.za>**

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PRELIMINARY DRAFT

ANDREW ROOS

VIRONIX SOFTWARE LABORATORIES

## 1. INTRODUCTION

This paper discusses a class of weak keys in RSA’s RC4 stream cipher. It shows

that for at least 1 out of every 256 possible keys the initial byte of the

pseudo-random stream generated by RC4 is strongly correlated with only a few

bytes of the key, which effecitively reduces the work required to exhaustively

search RC4 key spaces.

## 2. STATE TABLE INITIALIZATION IN RC4

Although the RC4 algorithm has not been published by RSA Data Security, source

code to implement the algorithm was anonymously posted to the Cypherpunks

mailing list several months ago. The success of the Cypherpunks’ brute-force

attack on SSL with a 40-bit key indicates that the source code published did

accurately implement RC4.

RC4 uses a variable length key from 1 to 256 bytes to initialize a 256-byte

state table which is used for the subsequent generation of pseudo-random bytes.

The state table is first initialized to the sequence {0,1,2,…,255}. Then:

1 index1 = 0; 2 index2 = 0; 3 4 for(counter = 0; counter < 256; counter++) 5 { 6 index2 = (key_data_ptr[index1] + state[counter] + index2) % 256; 7 swap_byte(&state[counter], &state[index2]); 8 index1 = (index1 + 1) % key_data_len; 9 }

Note that the only line which directly affects the state table is line 7, when

two bytes in the table are exchanged. The first byte is indexed by “counter”,

which is incremented for each iteration of the loop. The second byte is

indexed by “index2” which is a function of the key. Hence each element of the

state table will be swapped at least once (although possibly with itself),

when it is indexed by “counter”. It may also be swapped zero, one or more

times when it is indexed by “index2”. If we assume for the moment that

“index2” is a uniformly distributed pseudo-random number, then the probability

that a particular single element of the state table will be indexed by

“index2” at some time during the initialization routine is:

P = 1 - (255/256) ^ 255 = 0.631

(The exponent is 255 because we can disregard the case when “index2” and

“counter” both index the same element, since this will not affect its value.)

Conversely, there is a 37% probability that a particular element will *_not_* be

indexed by “index2” during initialization, so its final value in the state

table will only be affected by a single swap, when it is indexed by “counter”.

Since key bytes are used sequentially (starting again at the beginning when the

key is exhausted), this implies:

A. Given a key length of K bytes, and E < K, there is a 37% probability that element E of the state table depends only on elements 0..E (inclusive) of the key.

(This is approximate since “index2” is unlikely to be uniformly distributed.)

In order to make use of this, we need to determine the most likely values for

elements of the state table. Since each element is swapped at least once (when

it is indexed by “counter”), it is necessary to take into account the likely

effect of this swap. Swapping is a nasty non-linear process which is hard to

analyze. However, when dealing with the first few elements of the state table,

there is a high probability that the byte with which the element is swapped

has not itself been involved in any previous exchanges, and therefore retains

its initial value {0,1,2,…,255}. Similarly, when dealing with the first few

elements of the state table, there is also a significant probability that none

of the state elements added to index2 in line 6 of the algorithm has been

swapped either.

This means that the most likely value of an element in the state table can be

estimated by assuming that state[x] == x in the algorithm above. In this case,

the algorithm becomes:

1 index1 = 0; 2 index2 = 0; 3 4 for(counter = 0; counter < 256; counter++) 5 { 6 index2 = (key_data_ptr[index1] + counter + index2) % 256; 7 state[counter] = index2; 8 index1 = (index1 + 1) % key_data_len; 9 }

Which can be reduced to:

B. The most likely value for element E of the state table is: S[E] = X(E) + E(E+1)/2 where X(E) is the sum of bytes 0..E (inclusive) of the key.

(when calculating the sum of key elements, the key is considered to “wrap

around” on itself).

Given this analysis, we can calculate the probability for each element of the

state table that it’s value is the “most likely value” of B above. The easiest

way to do this is to evaluate the state tables produced from a number of

pseudo-randomly generated RC4 keys. The following table shows the results for

the first 47 elements from a trial of 100 000 eighty-bit RC4 keys:

Probability (%) 0-7 37.0 36.8 36.2 35.8 34.9 34.0 33.0 32.2 8-15 30.9 29.8 28.5 27.5 26.0 24.5 22.9 21.6 16-23 20.3 18.9 17.3 16.1 14.7 13.5 12.4 11.2 24-31 10.1 9.0 8.2 7.4 6.4 5.7 5.1 4.4 32-39 3.9 3.5 3.0 2.6 2.3 2.0 1.7 1.4 40-47 1.3 1.2 1.0 0.9 0.8 0.7 0.6 0.6

The table confirms that there is a significant correlation between the first

few values in the state table and the “likely value” predicted by B.

## 3. WEAK KEYS

The RC4 state table is used to generate a pseudo-random stream which is XORed

with the plaintext to give the ciphertext. The algorithm used to generate the

stream is as follows:

x and y are initialized to 0. To generate each byte: 1 x = (x + 1) % 256; 2 y = (state[x] + y) % 256; 3 swap_byte(&state[x], &state[y]); 4 xorIndex = (state[x] + state[y]) % 256; 5 GeneratedByte = state[xorIndex];

One way to exploit our analysis of the state table is to find circumstances

under which one or more generated bytes are strongly correlated with a small

subset of the key bytes.

Consider what happens when generating the first byte if state[1] == 1.

1 x = (0 + 1) % 256; /* x == 1 */ 2 y = (state[1] + 0) % 256; /* y == 1 */ 3 swap_byte(&state[1], &state[1]); /* no effect */ 4 xorIndex = (state[1] + state[1]); /* xorIndex = 2 */ 5 GeneratedByte = state[2]

And we know that state[2] is has a high probability of being

S[2] = K[0] + K[1] + K[2] + 2 (2+1) / 2

Similarly,

S[1] = K[0] + K[1] + 1 (1+1) / 2

So to make it probable that S[1] == 1, we have:

K[0] + K[1] == 0 (mod 256)

In which case the most likely value for S[2] is:

S[2] = K[2] + 3

This allows us to identify a class of weak keys:

C. Given an RC4 key K[0]..K[N] with K[0] + K[1] == 0 (mod 256), there is a significant probability that the first byte generated by RC4 will be K[2] + 3 (mod 256).

Note that there are two special cases, caused by “unexpected” swapping during

key generation. When K[0]==1, the “expected” output byte is k[2] + 2, and when

k[0]==2, the expected value is k[2] + 1.

There are a number of similar classes of “weak keys” which only affect a few

keys out of every 65536. However the particular symmetry in this class means

that it affects one key in 256, making it the most interesting instance.

Once again I took the easy way out and used simulation to determine the

approximate probability that result C holds for any given key. Probabilities

ranged between 12% and 16% depending on the values of K[0] and K[1], with a

mean of about 13.8%. All these figures are significantly greater than the

0.39% which would be expected from an uncorrelated generator. The key length

used was again 80 bits. This works the other way around as well: given the

first byte B[0] generated by a weak key, the probability that K[2]==B[0]-3

(mod 256) is 13.8%.

## 4. EXPLOITING WEAK KEYS IN RC4

Having found a class of weak keys, we need a practical way to attack RC4 based

cryptosystems using them. The most obvious way would be to search potential

weak keys first during an exhaustive attack. However since only one in every

256 keys is weak, the effective reduction in search space is not particularly

significant.

The usefulness of weak keys does increase if the opponent is satisfied with

recovering only a percentage of the keys subjected to analysis. Given a known

generator output which includes the first generated byte, one could assume

that the key was weak and search only the weak keys which would generate the

known initial byte. Since 1 in 256 keys is weak, and there is a 13.8% chance

that the assumed value of K[2] will be correct, there is only a 0.054% chance

of finding the key this way. However, you have reduced the search space by 16

bits due to the assumed relationship between K[0] and K[1] and the assumed

value of K[2], so the work factor per key recovered is reduced by a factor of

35, which is equivalent reducing the effective key length by 5.1 bits.

However in particular circumstances, the known relationships between weak keys

may provide a much more significant reduction in workload. The remainder of

this section describes an attack which, although requiring very specific

conditions, illustrates the potential threat.

As a stream cipher, a particular RC4 key can only be used once. When multiple

communications sessions are required, some mechanism must be provided for

generating a new session key each time. Let us suppose that an implementation

chose the simple method of incrementing the previous session key to get the

new session key, and that the session key was treated as a “little endian”

(least significant byte first) integer for this purpose.

We now have the interesting situation that the session keys will “cycle

through” weak keys in a pattern which repeats every 2^16 keys:

00 00 00 ... Weak (510 non-weak keys) FF 01 00 ... Weak (254 non-weak keys) FE 02 00 ... Weak (254 non-weak keys) FD 03 00 ... Weak ... 01 FF 00 ... Weak (254 non-weak keys) 00 00 01 ... Weak (510 non-weak keys) FF 01 01 ... Weak

(Least significant byte on the left)

Now while an isolated weak key cannot be identified simply from a known

generator output, this cycle of weak keys at known intervals can be identified

using statistical techniques since each of the weak keys has a higher than

expected probability of generating the *_same_* initial byte. This means that an

opponent who knew the initial generated bytes of about 2^16 session keys could

identify the weak keys, and would also be able to locate the 510-key gap

between successive cycles of weak keys (although not precisely). Since the

510-key gap occurs immediately following a key which begins with 00 00, the

opponent not only knows that the keys are weak, but also knows the first two

bytes of each key. The third byte of each key can be guessed from the first

output byte generated by the key, with a 13.8% chance of a correct guess.

Assuming that the “510-key gap” is narrowed down to 1 of 8 weak keys, the

attacker can search a key space which is 24 bits less than the size of the

session keys, with a 13.8%/8 chance of success, effectively reducing the key

space by approximately 18 bits.

Although this particular attack depends on a very specific set of

circumstances, it is likely that other RC4 based cryptosystems in which there

are linear relationships between successive session keys could be vulnerable

to similar attacks.

## 5. RECOMMENDATIONS

The attacks described in this algorithm result from inadequate “mixing” of key

bytes during the generation of the RC4 state table. The following measures

could be taken to strengthen cryptosystems based on the RC4 algorithm:

(a) After initializing the algorithm, generate and discard a number of bytes. Since the algorithm used to generate bytes also introduces additional non-linear dependencies into the state table, this would make analysis more difficult. (b) In systems which require multiple session keys, ensure that session keys are not linearly related to each other. (c) Avoid using the weak keys described.

## 6. CONCLUSION

This preliminary analysis of RC4 shows that the algorithm is vulnerable to

analytic attacks based on statistical analysis of its state table. It is

likely that a more detailed analysis of the algorithm will reveal more

effective ways to exploit the weaknesses described.

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