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Observable Discrepancy

Incomplete Base
Structure: Simple
Description

The 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.

Extended Description

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.
Common Consequences 2
Scope: ConfidentialityAccess Control

Impact: Read Application DataBypass Protection Mechanism

An attacker can gain access to sensitive information about the system, including authentication information that may allow an attacker to gain access to the system.

Scope: Confidentiality

Impact: Read Application Data

When cryptographic primitives are vulnerable to side-channel-attacks, this could be used to reveal unencrypted plaintext in the worst case.
Potential Mitigations 2
Phase: Architecture and Design

Strategy: Separation of Privilege

Compartmentalize the system to have "safe" areas where trust boundaries can be unambiguously drawn. Do not allow sensitive data to go outside of the trust boundary and always be careful when interfacing with a compartment outside of the safe area. Ensure that appropriate compartmentalization is built into the system design, and the compartmentalization allows for and reinforces privilege separation functionality. Architects and designers should rely on the principle of least privilege to decide the appropriate time to use privileges and the time to drop privileges.
Phase: Implementation
Ensure that error messages only contain minimal details that are useful to the intended audience and no one else. The messages need to strike the balance between being too cryptic (which can confuse users) or being too detailed (which may reveal more than intended). The messages should not reveal the methods that were used to determine the error. Attackers can use detailed information to refine or optimize their original attack, thereby increasing their chances of success. If errors must be captured in some detail, record them in log messages, but consider what could occur if the log messages can be viewed by attackers. Highly sensitive information such as passwords should never be saved to log files. Avoid inconsistent messaging that might accidentally tip off an attacker about internal state, such as whether a user account exists or not.
Demonstrative Examples 4

ID : DX-38

The following code checks validity of the supplied username and password and notifies the user of a successful or failed login.

Code Example:

Bad
Perl
perl
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:

Code Example:

Result
bash

ID : DX-193

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.

Code Example:

Bad
Python
python
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.
Non-uniform processing time causes timing channel.

Code Example:

Bad
Other

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.

Code Example:

Good
Other

Artificial delays may be added to ensure that all calculations take equal time to execute.

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.
Observed Examples 23
CVE-2020-8695Observable discrepancy in the RAPL interface for some Intel processors allows information disclosure.
CVE-2019-14353Crypto hardware wallet's power consumption relates to total number of pixels illuminated, creating a side channel in the USB connection that allows attackers to determine secrets displayed such as PIN numbers and passwords
CVE-2019-10071Java-oriented framework compares HMAC signatures using String.equals() instead of a constant-time algorithm, causing timing discrepancies
CVE-2002-2094This, and others, use ".." attacks and monitor error responses, so there is overlap with directory traversal.
CVE-2001-1483Enumeration of valid usernames based on inconsistent responses
CVE-2001-1528Account number enumeration via inconsistent responses.
CVE-2004-2150User enumeration via discrepancies in error messages.
CVE-2005-1650User enumeration via discrepancies in error messages.
CVE-2004-0294Bulletin Board displays different error messages when a user exists or not, which makes it easier for remote attackers to identify valid users and conduct a brute force password guessing attack.
CVE-2004-0243Operating System, when direct remote login is disabled, displays a different message if the password is correct, which allows remote attackers to guess the password via brute force methods.
CVE-2002-0514Product allows remote attackers to determine if a port is being filtered because the response packet TTL is different than the default TTL.
CVE-2002-0515Product sets a different TTL when a port is being filtered than when it is not being filtered, which allows remote attackers to identify filtered ports by comparing TTLs.
CVE-2002-0208Product modifies TCP/IP stack and ICMP error messages in unusual ways that show the product is in use.
CVE-2004-2252Behavioral infoleak by responding to SYN-FIN packets.
CVE-2001-1387Product may generate different responses than specified by the administrator, possibly leading to an information leak.
CVE-2004-0778Version control system allows remote attackers to determine the existence of arbitrary files and directories via the -X command for an alternate history file, which causes different error messages to be returned.
CVE-2004-1428FTP server generates an error message if the user name does not exist instead of prompting for a password, which allows remote attackers to determine valid usernames.
CVE-2003-0078SSL implementation does not perform a MAC computation if an incorrect block cipher padding is used, which causes an information leak (timing discrepancy) that may make it easier to launch cryptographic attacks that rely on distinguishing between padding and MAC verification errors, possibly leading to extraction of the original plaintext, aka the "Vaudenay timing attack."
CVE-2000-1117Virtual machine allows malicious web site operators to determine the existence of files on the client by measuring delays in the execution of the getSystemResource method.
CVE-2003-0637Product uses a shorter timeout for a non-existent user than a valid user, which makes it easier for remote attackers to guess usernames and conduct brute force password guessing.
CVE-2003-0190Product immediately sends an error message when a user does not exist, which allows remote attackers to determine valid usernames via a timing attack.
CVE-2004-1602FTP server responds in a different amount of time when a given username exists, which allows remote attackers to identify valid usernames by timing the server response.
CVE-2005-0918Browser allows remote attackers to determine the existence of arbitrary files by setting the src property to the target filename and using Javascript to determine if the web page immediately stops loading, which indicates whether the file exists or not.
Applicable Platforms
Languages:
Not Language-Specific : Undetermined
Technologies:
Not Technology-Specific : Undetermined
Modes of Introduction
Architecture and Design
Implementation
Related Attack Patterns
Alternate Terms

Side Channel Attack

Observable Discrepancies are at the root of side channel attacks.
Related Weaknesses
ChildOf: Exposure of Sensitive Information to an Unauthorized Actor (CWE-200)
ChildOf: Exposure of Sensitive Information to an Unauthorized Actor (CWE-200)
Taxonomy Mapping
  • PLOVER
  • OWASP Top Ten 2007
  • OWASP Top Ten 2004