CryptGenRandom

A cryptanalysis of CryptGenRandom, published in November 2007 by Leo Dorrendorf and others from the Hebrew University of Jerusalem and University of Haifa, found significant weaknesses in the Windows 2000 implementation of the algorithm.[5]

To take advantage of the vulnerability, an attacker would first need to compromise the program running the random number generator. The weaknesses in the paper all depend on an attacker siphoning the state bits out of the generator. An attacker in a position to carry out this attack would typically already be in a position to defeat any random number generator (for instance, they can simply sniff the outputs of the generator, or fix them in memory to known values). However, the Hebrew University team notes that an attacker only need steal the state bits once in order to persistently violate the security of a CryptGenRandom instance. They can also use the information they glean to determine past random numbers that were generated, potentially compromising information, such as credit card numbers, already sent.

The paper's attacks are based on the fact that CryptGenRandom uses the stream cipher RC4, which can be run backwards once its state is known. They also take advantage of the fact that CryptGenRandom runs in user mode, allowing anyone who gains access to the operating system at user level, for example by exploiting a buffer overflow, to get CryptGenRandom's state information for that process. Finally, CryptGenRandom refreshes its seed from entropy infrequently. This problem is aggravated by the fact that each Win32 process has its own instance of CryptGenRandom state; while this means that a compromise of one process does not transitively compromise every other process, it may also increase the longevity of any successful break.

Because the details of the CryptGenRandom algorithm are not public, Dorrendorf's team used reverse engineering tools to discern how the algorithm works. Their paper is the first published record of how the Windows cryptographic random number generator operates.

Windows 2000, XP and 2003 have all successfully undergone EAL4+ evaluations, including the CryptGenRandom() and FIPSGenRandom() implementations. The Security Target documentation is available at the Common Criteria Portal, and indicates compliance with the EAL4 requirements. Few conclusions can be drawn about the security of the algorithm as a result; EAL4 measures products against best practices and stated security objectives, but rarely involves in-depth cryptanalysis.

Microsoft has obtained validation of its RNG implementations in the following environments:

• Windows Vista RNG implementations (certificate 321)[6]
• Windows 2003 Enhanced Cryptographic Provider (rsaenh.dll) (certificate 316)[6]
• Windows 2003 Enhanced DSS and Diffie-Hellman Cryptographic Provider (dssenh.dll) (certificate 314)[6]
• Windows 2003 Kernel Mode Cryptographic Module (fips.sys) (certificate 313)[6]
• Windows CE and Windows Mobile Enhanced Cryptographic Provider (rsaenh.dll) (certificate 292)[6]
• Windows CE and Windows Mobile Enhanced Cryptographic Provider (rsaenh.dll) (certificate 286)[6]
• Windows CE Enhanced Cryptographic Provider (rsaenh.dll) (certificate 66)[6]

These tests are "designed to test conformance to the various approved RNG specifications rather than provide a measure of a product’s security. [...] Thus, validation should not be interpreted as an evaluation or endorsement of overall product security." Few conclusions can be drawn about the security of the algorithm as a result; FIPS evaluations do not necessarily inspect source code or evaluate the way RNG seeds are generated.[7]

Windows developers have several alternative means of accessing the CryptGenRandom functionality; these alternatives invoke the same algorithm and share the same security characteristics, but may have other advantages.

Historically, we always told developers not to use functions such as rand to generate keys, nonces and passwords, rather they should use functions like CryptGenRandom, which creates cryptographically secure random numbers. The problem with CryptGenRandom is you need to pull in CryptoAPI (CryptAcquireContext and such) which is fine if you're using other crypto functions.

On a default Windows XP and later install, CryptGenRandom calls into a function named ADVAPI32!RtlGenRandom, which does not require you load all the CryptAPI stuff. In fact, the new Whidbey CRT function, rand_s calls RtlGenRandom.[8]

Programmers using .NET should use the RNGCryptoServiceProvider Class.[9]

The CNG [10] is a long term replacement for the deprecated Crypto API. It provides an equivalent function BCryptGenRandom[11] as well as dedicated functions for key generation.

• the Microsoft C++ library function rand_s uses RtlGenRandom and is recommended by Microsoft for secure applications.[12]
• the Python function urandom in the os module, which uses /dev/urandom on Unix-like systems, calls CryptGenRandom on Windows systems.[13]
• the Java JCA Provider "SunMSCAPI" available with OpenJDK and Oracle distributions of the JRE on Windows provides a SecureRandom implementation with the algorithm name Windows-PRNG. This class forwards all queries for random or seed bytes as well as setting additional seed bytes to native CryptGenRandom.[14]