Covert timing channels convey information by modulating some aspect of system behavior over time, so that the program receiving the information can observe system behavior and infer protected information.
In some instances, knowing when data is transmitted between parties can provide a malicious user with privileged information. Also, externally monitoring the timing of operations can potentially reveal sensitive data. For example, a cryptographic operation can expose its internal state if the time it takes to perform the operation varies, based on the state.
Covert channels are frequently classified as either storage or timing channels. Some examples of covert timing channels are the system's paging rate, the time a certain transaction requires to execute, and the time it takes to gain access to a shared bus.
The table(s) below shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
Relevant to the view "Research Concepts" (CWE-1000)
The different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the software life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.
The listings below show possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.
Class: Language-Independent (Undetermined Prevalence)
The table below specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.
In this example, the attacker observes how long an authentication takes when the user types in the correct password.
When the attacker tries their own values, they can first try strings of various length. When they find a string of the right length, the computation will take a bit longer, because the for loop will run at least once. Additionally, with this code, the attacker can possibly learn one character of the password at a time, because when they guess the first character right, the computation will take longer than a wrong guesses. Such an attack can break even the most sophisticated password with a few hundred guesses.
Example Language: Python
def validate_password(actual_pw, typed_pw):
if len(actual_pw) <> len(typed_pw):
for i in len(actual_pw):
if actual_pw[i] <> typed_pw[i]:
Note that, in this example, the actual password must be handled in constant time, as far as the attacker is concerned, even if the actual password is of an unusual length. This is one reason why it is good to use an algorithm that, among other things, stores a seeded cryptographic one-way hash of the password, then compare the hashes, which will always be of the same length.
This MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
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