Common Weakness Enumeration

This can have security implications when the expected synchronization is in security-critical code, such as recording whether a user is authenticated or modifying important state information that should not be influenced by an outsider.

A race condition occurs within concurrent environments, and is effectively a property of a code sequence. Depending on the context, a code sequence may be in the form of a function call, a small number of instructions, a series of program invocations, etc.

A race condition violates these properties, which are closely related:

• Exclusivity - the code sequence is given exclusive access to the shared resource, i.e., no other code sequence can modify properties of the shared resource before the original sequence has completed execution.
• Atomicity - the code sequence is behaviorally atomic, i.e., no other thread or process can concurrently execute the same sequence of instructions (or a subset) against the same resource.

A race condition exists when an "interfering code sequence" can still access the shared resource, violating exclusivity. Programmers may assume that certain code sequences execute too quickly to be affected by an interfering code sequence; when they are not, this violates atomicity. For example, the single "x++" statement may appear atomic at the code layer, but it is actually non-atomic at the instruction layer, since it involves a read (the original value of x), followed by a computation (x+1), followed by a write (save the result to x).

The interfering code sequence could be "trusted" or "untrusted." A trusted interfering code sequence occurs within the product; it cannot be modified by the attacker, and it can only be invoked indirectly. An untrusted interfering code sequence can be authored directly by the attacker, and typically it is external to the vulnerable product.

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.

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Example 1

This code could be used in an e-commerce application that supports transfers between accounts. It takes the total amount of the transfer, sends it to the new account, and deducts the amount from the original account.

A race condition could occur between the calls to GetBalanceFromDatabase() and SendNewBalanceToDatabase().

Suppose the balance is initially 100.00. An attack could be constructed as follows:

At this stage, the attacker should have a balance of 19.00 (due to 81.00 worth of transfers), but the balance is 99.00, as recorded in the database.

To prevent this weakness, the programmer has several options, including using a lock to prevent multiple simultaneous requests to the web application, or using a synchronization mechanism that includes all the code between GetBalanceFromDatabase() and SendNewBalanceToDatabase().

Example 2

The following function attempts to acquire a lock in order to perform operations on a shared resource.

However, the code does not check the value returned by pthread_mutex_lock() for errors. If pthread_mutex_lock() cannot acquire the mutex for any reason, the function may introduce a race condition into the program and result in undefined behavior.

In order to avoid data races, correctly written programs must check the result of thread synchronization functions and appropriately handle all errors, either by attempting to recover from them or reporting them to higher levels.

Example 3

Suppose a processor's Memory Management Unit (MMU) has 5 other shadow MMUs to distribute its workload for its various cores. Each MMU has the start address and end address of "accessible" memory. Any time this accessible range changes (as per the processor's boot status), the main MMU sends an update message to all the shadow MMUs.

Suppose the interconnect fabric does not prioritize such "update" packets over other general traffic packets. This introduces a race condition. If an attacker can flood the target with enough messages so that some of those attack packets reach the target before the new access ranges gets updated, then the attacker can leverage this scenario.

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.

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Technologies

Example 1

This example PHP code attempts to secure the form submission process by validating that the user submitting the form has a valid session. A CSRF attack would not be prevented by this countermeasure because the attacker forges a request through the user's web browser in which a valid session already exists.

The following HTML is intended to allow a user to update a profile.

profile.php contains the following code.

This code may look protected since it checks for a valid session. However, CSRF attacks can be staged from virtually any tag or HTML construct, including image tags, links, embed or object tags, or other attributes that load background images.

The attacker can then host code that will silently change the username and email address of any user that visits the page while remaining logged in to the target web application. The code might be an innocent-looking web page such as:

Notice how the form contains hidden fields, so when it is loaded into the browser, the user will not notice it. Because SendAttack() is defined in the body's onload attribute, it will be automatically called when the victim loads the web page.

Assuming that the user is already logged in to victim.example.com, profile.php will see that a valid user session has been established, then update the email address to the attacker's own address. At this stage, the user's identity has been compromised, and messages sent through this profile could be sent to the attacker's address.

It is often convenient to serialize objects for communication or to save them for later use. However, deserialized data or code can often be modified without using the provided accessor functions if it does not use cryptography to protect itself. Furthermore, any cryptography would still be client-side security -- which is a dangerous security assumption.

Data that is untrusted can not be trusted to be well-formed.

When developers place no restrictions on "gadget chains," or series of instances and method invocations that can self-execute during the deserialization process (i.e., before the object is returned to the caller), it is sometimes possible for attackers to leverage them to perform unauthorized actions, like generating a shell.

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.

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Technologies

Example 1

This code snippet deserializes an object from a file and uses it as a UI button:

This code does not attempt to verify the source or contents of the file before deserializing it. An attacker may be able to replace the intended file with a file that contains arbitrary malicious code which will be executed when the button is pressed.

To mitigate this, explicitly define final readObject() to prevent deserialization. An example of this is:

Example 2

In Python, the Pickle library handles the serialization and deserialization processes. In this example derived from [REF-467], the code receives and parses data, and afterwards tries to authenticate a user based on validating a token.

Unfortunately, the code does not verify that the incoming data is legitimate. An attacker can construct a illegitimate, serialized object "AuthToken" that instantiates one of Python's subprocesses to execute arbitrary commands. For instance,the attacker could construct a pickle that leverages Python's subprocess module, which spawns new processes and includes a number of arguments for various uses. Since Pickle allows objects to define the process for how they should be unpickled, the attacker can direct the unpickle process to call Popen in the subprocess module and execute /bin/sh.

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

Technologies

Example 1

The following code intends to ensure that the user is already logged in. If not, the code performs authentication with the user-provided username and password. If successful, it sets the loggedin and user cookies to "remember" that the user has already logged in. Finally, the code performs administrator tasks if the logged-in user has the "Administrator" username, as recorded in the user cookie.

Unfortunately, this code can be bypassed. The attacker can set the cookies independently so that the code does not check the username and password. The attacker could do this with an HTTP request containing headers such as:

By setting the loggedin cookie to "true", the attacker bypasses the entire authentication check. By using the "Administrator" value in the user cookie, the attacker also gains privileges to administer the software.

Example 2

In January 2009, an attacker was able to gain administrator access to a Twitter server because the server did not restrict the number of login attempts [REF-236]. The attacker targeted a member of Twitter's support team and was able to successfully guess the member's password using a brute force attack by guessing a large number of common words. After gaining access as the member of the support staff, the attacker used the administrator panel to gain access to 33 accounts that belonged to celebrities and politicians. Ultimately, fake Twitter messages were sent that appeared to come from the compromised accounts.

Example 3

In 2022, the OT:ICEFALL study examined products by 10 different Operational Technology (OT) vendors. The researchers reported 56 vulnerabilities and said that the products were "insecure by design" [REF-1283]. If exploited, these vulnerabilities often allowed adversaries to change how the products operated, ranging from denial of service to changing the code that the products executed. Since these products were often used in industries such as power, electrical, water, and others, there could even be safety implications.

Multiple vendors did not use any authentication or used client-side authentication for critical functionality in their OT products.

• Authentication

When a product allows a user's input to contain code syntax, it might be possible for an attacker to craft the code in such a way that it will alter the intended control flow of the product. Such an alteration could lead to arbitrary code execution.

Injection problems encompass a wide variety of issues -- all mitigated in very different ways. For this reason, the most effective way to discuss these weaknesses is to note the distinct features which classify them as injection weaknesses. The most important issue to note is that all injection problems share one thing in common -- i.e., they allow for the injection of control plane data into the user-controlled data plane. This means that the execution of the process may be altered by sending code in through legitimate data channels, using no other mechanism. While buffer overflows, and many other flaws, involve the use of some further issue to gain execution, injection problems need only for the data to be parsed. The most classic instantiations of this category of weakness are SQL injection and format string vulnerabilities.

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

Technologies

Example 1

This example attempts to write user messages to a message file and allow users to view them.

While the programmer intends for the MessageFile to only include data, an attacker can provide a message such as:

which will decode to the following:

The programmer thought they were just including the contents of a regular data file, but PHP parsed it and executed the code. Now, this code is executed any time people view messages.

Notice that XSS (CWE-79) is also possible in this situation.

Example 2

edit-config.pl: This CGI script is used to modify settings in a configuration file.

The script intends to take the 'action' parameter and invoke one of a variety of functions based on the value of that parameter - config_file_add_key(), config_file_set_key(), or config_file_delete_key(). It could set up a conditional to invoke each function separately, but eval() is a powerful way of doing the same thing in fewer lines of code, especially when a large number of functions or variables are involved. Unfortunately, in this case, the attacker can provide other values in the action parameter, such as:

This would produce the following string in handleConfigAction():

Any arbitrary Perl code could be added after the attacker has "closed off" the construction of the original function call, in order to prevent parsing errors from causing the malicious eval() to fail before the attacker's payload is activated. This particular manipulation would fail after the system() call, because the "_key(\$fname, \$key, \$val)" portion of the string would cause an error, but this is irrelevant to the attack because the payload has already been activated.

Example 3

This simple script asks a user to supply a list of numbers as input and adds them together.

The eval() function can take the user-supplied list and convert it into a Python list object, therefore allowing the programmer to use list comprehension methods to work with the data. However, if code is supplied to the eval() function, it will execute that code. For example, a malicious user could supply the following string:

This would delete all the files in the current directory. For this reason, it is not recommended to use eval() with untrusted input.

A way to accomplish this without the use of eval() is to apply an integer conversion on the input within a try/except block. If the user-supplied input is not numeric, this will raise a ValueError. By avoiding eval(), there is no opportunity for the input string to be executed as code.

An alternative, commonly-cited mitigation for this kind of weakness is to use the ast.literal_eval() function, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].

Input validation is a frequently-used technique for checking potentially dangerous inputs in order to ensure that the inputs are safe for processing within the code, or when communicating with other components. When software does not validate input properly, an attacker is able to craft the input in a form that is not expected by the rest of the application. This will lead to parts of the system receiving unintended input, which may result in altered control flow, arbitrary control of a resource, or arbitrary code execution.

Input validation is not the only technique for processing input, however. Other techniques attempt to transform potentially-dangerous input into something safe, such as filtering (CWE-790) - which attempts to remove dangerous inputs - or encoding/escaping (CWE-116), which attempts to ensure that the input is not misinterpreted when it is included in output to another component. Other techniques exist as well (see CWE-138 for more examples.)

Input validation can be applied to:

• raw data - strings, numbers, parameters, file contents, etc.
• metadata - information about the raw data, such as headers or size

Data can be simple or structured. Structured data can be composed of many nested layers, composed of combinations of metadata and raw data, with other simple or structured data.

Many properties of raw data or metadata may need to be validated upon entry into the code, such as:

• specified quantities such as size, length, frequency, price, rate, number of operations, time, etc.
• implied or derived quantities, such as the actual size of a file instead of a specified size
• indexes, offsets, or positions into more complex data structures
• symbolic keys or other elements into hash tables, associative arrays, etc.
• well-formedness, i.e. syntactic correctness - compliance with expected syntax
• lexical token correctness - compliance with rules for what is treated as a token
• specified or derived type - the actual type of the input (or what the input appears to be)
• consistency - between individual data elements, between raw data and metadata, between references, etc.
• conformance to domain-specific rules, e.g. business logic
• equivalence - ensuring that equivalent inputs are treated the same
• authenticity, ownership, or other attestations about the input, e.g. a cryptographic signature to prove the source of the data

Implied or derived properties of data must often be calculated or inferred by the code itself. Errors in deriving properties may be considered a contributing factor to improper input validation.

Note that "input validation" has very different meanings to different people, or within different classification schemes. Caution must be used when referencing this CWE entry or mapping to it. For example, some weaknesses might involve inadvertently giving control to an attacker over an input when they should not be able to provide an input at all, but sometimes this is referred to as input validation.

Finally, it is important to emphasize that the distinctions between input validation and output escaping are often blurred, and developers must be careful to understand the difference, including how input validation is not always sufficient to prevent vulnerabilities, especially when less stringent data types must be supported, such as free-form text. Consider a SQL injection scenario in which a person's last name is inserted into a query. The name "O'Reilly" would likely pass the validation step since it is a common last name in the English language. However, this valid name cannot be directly inserted into the database because it contains the "'" apostrophe character, which would need to be escaped or otherwise transformed. In this case, removing the apostrophe might reduce the risk of SQL injection, but it would produce incorrect behavior because the wrong name would be recorded.