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SILC Toolkit Reference Manual SILC Core Library SILC Authentication Interface SILC Message Interface SILC Channel Interface SILC Command Interface SILC Notify Interface SILC Status Types SILC Modes SILC ID Interface SILC ID Cache Interface SILC Argument Interface SILC Attributes Interface Packet Protocol Interface SILC Utility Library Basic SILC Types SILC Buffer Interface SILC Buffer Format Interface SILC Hash Table Interface SILC Logging Interface SILC Memory Interface SILC Mutex Interface SILC Thread Interface SILC Network Interface SILC Schedule Interface SILC Socket Interface SILC Protocol Interface SILC Config Interface SILC File Util Interface SILC String Util Interface SILC UTF-8 Interface SILC Util Interface SILC List Interface SILC Dynamic List Interface SILC VCard Interface SILC Application Utilities SILC Crypto Library Introduction to SILC RNG SILC RNG Interface SILC Cipher API SILC PKCS API SILC PKCS#1 API SILC Hash Interface SILC HMAC Interface SILC SFTP Library SILC SFTP Interface SFTP Filesystems Interface SILC Client Library Using SILC Client Library Tutorial Arguments for command_reply Client Operation SilcStatus Error Arguments in command_reply Client Operation Arguments for notify Client Operation Unicode and UTF-8 Strings in Client Library Client Library Interface Reference SILC Key Exchange Library SILC SKE Interface SKE Status Types SKE Diffie Hellman Groups SKE Payloads SILC Math Library SILC MP Interface SILC Math Interface Resource Links SILC Project Website SILC Protocol Documentation SILC White Paper SILC FAQs
Introduction to Random Number Generator Overview SILC Random Number Generator is cryptographically strong pseudo random number generator. It is used to generate all the random numbers needed in the SILC sessions. All key material and other sources needing random numbers use this generator. The RNG has a random pool of 1024 bytes of size that provides the actual random numbers for the application. The pool is initialized when the RNG is allocated and initialized with silc_rng_alloc and silc_rng_init functions, respectively. Random Pool Initialization The RNG's random pool is the source of all random output data. The pool is initialized with silc_rng_init and application can reseed it at any time by calling the silc_rng_add_noise function. The initializing phase attempts to set the random pool in a state that it is impossible to learn the input data to the RNG or any random output data. This is achieved by acquiring noise from various system sources. The first source is called to provide "soft noise". This noise is various data from system's processes. The second source is called to provide "medium noise". This noise is various output data from executed commands. Usually the commands are Unix `ps' and `ls' commands with various options. The last source is called to provide "hard noise" and is noise from system's /dev/random, if it exists. Stirring the Random Pool Every time data is acquired from any source, the pool is stirred. The stirring process performs an CFB (cipher feedback) encryption with SHA1 algorithm to the entire random pool. First it acquires an IV (Initial Vector) from the constant (random) location of the pool and performs the first CFB pass. Then it acquires a new encryption key from variable location of the pool and performs the second CFB pass. The encryption key thus is always acquired from unguessable data. The encryption process to the entire random pool assures that it is impossible to learn the input data to the random pool without breaking the encryption process. This would effectively mean breaking the SHA1 hash function. The encryption process also assures that each random output from the random pool is secured with cryptographically strong function, the SHA1 in this case. The random pool can be restirred by the application at any point by calling the silc_rng_add_noise function. This function adds new noise to the pool and then stirs the entire pool. Stirring Thresholds The random pool has two thresholds that controls when the random pool needs more new noise and requires restirring. As previously mentioned, the application may do this by calling the silc_rng_add_noise. However, the RNG performs this also automatically. The first threshold gets soft noise from system and stirs the random pool. The threshold is reached after 64 bits of random data has been fetched from the RNG. After the 64 bits, the soft noise acquiring and restirring process is performed every 8 bits of random output data until the second threshold is reached. The second threshold gets hard noise from system and stirs the random pool. The threshold is reached after 160 bits of random output. After the noise is acquired (from /dev/urandom) the random pool is stirred and the thresholds are set to zero. The process is repeated again after 64 bits of output for first threshold and after 160 bits of output for the second threshold. Internal State of the Random Pool The random pool has also internal state that provides several variable distinct points to the random pool where the data is fetched. The state changes every 8 bits of output data and it is guaranteed that the fetched 8 bits of data is from distinct location compared to the previous 8 bits. It is also guaranteed that the internal state never wraps before restirring the entire random pool. The internal state means that the data is not fetched linearly from the pool, eg. starting from zero and wrapping at the end of the pool. The internal state is not dependent of any random data in the pool. The internal states are initialized (by default the pool is splitted to four different sections (states)) at the RNG initialization phase. The state's current position is added linearly and wraps at the the start of the next state. The states provides the distinct locations. Security Considerations The security of this random number generator, like of any other RNG's, depends of the initial state of the RNG. The initial state of the random number generators must be unknown to an adversary. This means that after the RNG is initialized it is required that the input data to the RNG and the output data to the application has no correlation of any kind that could be used to compromise the acquired random numbers or any future random numbers. It is, however, clear that the correlation exists but it needs to be hard to solve for an adversary. To accomplish this the input data to the random number generator needs to be secret. Usually this is impossible to achieve. That is why SILC's RNG acquires the noise from three different sources and provides for the application an interface to add more noise at any time. The first source ("soft noise") is known to the adversary but requires exact timing to get all of the input data. However, getting only partial data is easy. The second source ("medium noise") depends on the place of execution of the application. Getting at least partial data is easy but securing for example the user's home directory from outside access makes it harder. The last source ("hard noise") is considered to be the most secure source of data. An adversary is not considered to have any access on this data. This of course greatly depends on the operating system. These three sources are considered to be adequate since the random pool is relatively large and the output of each bit of the random pool is secured by cryptographically secure function, the SHA1 in CFB mode encryption. Furthermore the application may provide other random data, such as random key strokes or mouse movement to the RNG. However, it is recommended that the application would not be the single point of source for the RNG, in either intializing or reseeding phases later in the session. Good solution is probably to use both, the application's seeds and the RNG's own sources, equally. The RNG must also assure that any old or future random numbers are not compromised if an adversary would learn the initial input data (or any input data for that matter). The SILC's RNG provides good protection for this even if the some of the input bits would be compromised for old or future random numbers. The RNG reinitalizes (reseeds) itself using the thresholds after every 64 and 160 bits of output. This is considered to be adequate even if some of the bits would get compromised. Also, the applications that use the RNG usually fetches at least 256 bits from the RNG. This means that everytime RNG is accessed both of the thresholds are reached. This should mean that the RNG is never too long in an compromised state and recovers as fast as possible. Caveat Windows Programmer The caller must be cautios when using this RNG with native WIN32 system. The RNG most likely is impossible to set in unguessable state just by using the RNG's input data sources. On WIN32 it is stronly suggested that caller would add more random noise after the initialization of the RNG using the silc_rng_add_noise function. For example, random mouse movements may be used.

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