CWE-203: Observable Discrepancy
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Edit Custom FilterThe product behaves differently or sends different responses under different circumstances in a way that is observable to an unauthorized actor, which exposes security-relevant information about the state of the product, such as whether a particular operation was successful or not.
Discrepancies can take many forms, and variations may be detectable in timing, control flow, communications such as replies or requests, or general behavior. These discrepancies can reveal information about the product's operation or internal state to an unauthorized actor. In some cases, discrepancies can be used by attackers to form a side channel.
This table 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.
This table 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)
Relevant to the view "Weaknesses for Simplified Mapping of Published Vulnerabilities" (CWE-1003)
Relevant to the view "Hardware Design" (CWE-1194)
The different Modes of Introduction provide information
about how and when this
weakness may be introduced. The Phase identifies a point in the life cycle at which
introduction
may occur, while the Note provides a typical scenario related to introduction during the
given
phase.
This listing shows 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.
Languages Class: Not Language-Specific (Undetermined Prevalence) Technologies Class: Not Technology-Specific (Undetermined Prevalence) Example 1 The following code checks validity of the supplied username and password and notifies the user of a successful or failed login. (bad code)
Example Language: Perl
my $username=param('username');
my $password=param('password'); if (IsValidUsername($username) == 1) { if (IsValidPassword($username, $password) == 1)
}
{ print "Login Successful";
}
else { print "Login Failed - incorrect password";
}
else { print "Login Failed - unknown username";
}
In the above code, there are different messages for when an incorrect username is supplied, versus when the username is correct but the password is wrong. This difference enables a potential attacker to understand the state of the login function, and could allow an attacker to discover a valid username by trying different values until the incorrect password message is returned. In essence, this makes it easier for an attacker to obtain half of the necessary authentication credentials. While this type of information may be helpful to a user, it is also useful to a potential attacker. In the above example, the message for both failed cases should be the same, such as: (result)
"Login Failed - incorrect username or password"
Example 2 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. (bad code)
Example Language: Python
def validate_password(actual_pw, typed_pw):
if len(actual_pw) <> len(typed_pw):
return 0
for i in len(actual_pw): if actual_pw[i] <> typed_pw[i]:
return 0
return 1 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. Example 3 Non-uniform processing time causes timing channel. (bad code)
Suppose an algorithm for implementing an encryption routine works fine per se, but the time taken to output the result of the encryption routine depends on a relationship between the input plaintext and the key (e.g., suppose, if the plaintext is similar to the key, it would run very fast).
In the example above, an attacker may vary the inputs, then observe differences between processing times (since different plaintexts take different time). This could be used to infer information about the key. (good code)
Artificial delays may be added to ensured all calculations take equal time to execute.
Example 4 Suppose memory access patterns for an encryption routine are dependent on the secret key. An attacker can recover the key by knowing if specific memory locations have been accessed or not. The value stored at those memory locations is irrelevant. The encryption routine's memory accesses will affect the state of the processor cache. If cache resources are shared across contexts, after the encryption routine completes, an attacker in different execution context can discover which memory locations the routine accessed by measuring the time it takes for their own memory accesses to complete.
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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