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An even easier rule to apply to identify this particular bug and likely others is to use static analysis to identify every use of a bad random number generator Although there are applications for statistical random number generators, the cost of producing a limited number of high-quality cryptographically strong random numbers is small enough that little practical justi cation exists for using statistical algorithms The following structural rule ags calls to any of the statistical random number generators in the standard C library mentioned at the beginning of this section:

Structural rule:



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Implementing a Message Inspector for Service Endpoint Behavior Listing 523 implements a logging behavior by printing out every message sent and received by an endpoint The code shows a message inspector called from an endpoint behavior This also shows how the endpoint behavior is manually added to the service description in a custom hosted service

RMI specific overheads, consisting of JRMP or IIOP protocol overhead and method dispatching overhead DGC overheads (JRMP only) in the case of JRMP, overheads due to Java Serialization; in the case of GIOP, overheads due to GIOP marshalling and unmarshalling serialization overheads specifically due to not declaring a serialVersionUID in a Serializable class, forcing it to be computed at runtime DNS delays due to misconfiguration at the client[10]





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FunctionCall fc: (fcfunction is [name name name name name name name name == == == == == == == == "rand" or "rand" or "srand" or "srand48" or "drand48" or "lrand48" or "random" or "srandom"])

The term entropy originates in the eld of thermodynamics, where it is used as a measure of the disorder in a system In mathematics and computer science, the term carries the same implications Because computers are designed to be deterministic machines, they cannot generate entropy Therefore, outside sources of entropy are critical for computers to be capable of generating values that are hard to guess

In practice, if you re implementing a message inspector for diagnostic purposes, see 10, Exception Handling, for tracing techniques

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You care about unpredictability only from the attacker s point of view; sources of information that an attacker knows do not provide any randomness For example, an attacker probably knows the time to within some reasonable precision He might be able to ascertain clock skew fairly precisely, too [Arkin et al, 1999] Outgoing mail from the target machine contains the time of day in the mail headers, and the TCP time stamp option might reveal even more If the attacker can estimate your clock down to the millisecond, then even if your clock has true microsecond accuracy, it provides only 10 bits of entropy More generally, if the attacker can predict a value down to an ambiguity of N possible choices, then that s lg(N) bits of entropy

[10]

Any estimate of entropy is valid only for a given threat model In other words, you have to consider the ways things can go wrong so that you can account for them in your estimate For example, we might usually assume that the attacker can eavesdrop on network traf c In this case, any value sent over the network is known to the attacker and Continues

The class implements the interface In its and it impleprints out the message to the console The class interface In its ments the method it adds the class to the list of message inspectors to be called with each message Finally, the main program adds the class to the list of behaviors on all endpoints Note that because the service also has a MEX endpoint, the request and response to that endpoint is also printed by

Continued contributes 0 bits of entropy If the attacker can send you packets, anything received from the network also counts for 0 bits of entropy Consider a less obvious example: Suppose you are collecting the time each key is pressed and feeding interkeystroke timings into your PRNG If the keystrokes are generated by a user connected through SSH, you cannot count on this source to provide any entropy whatsoever because an attacker can eavesdrop on the interpacket timings and deduce the interkeystroke timing values being fed to your PRNG In most cases, network-related data should be viewed as contributing very little or no entropy

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