Common Weakness Enumeration

Strategy: Input Validation

Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.

When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."

Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

Mitigation of resource exhaustion attacks requires that the target system either:

• recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays
• uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed.

The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.

The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.

If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery.

Ensure that all failures in resource allocation place the system into a safe posture.

Strategy: Resource Limitation

Use resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems.

When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users.

Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).

While fuzzing is typically geared toward finding low-level implementation bugs, it can inadvertently find uncontrolled resource allocation problems. This can occur when the fuzzer generates a large number of test cases but does not restart the targeted product in between test cases. If an individual test case produces a crash, but it does not do so reliably, then an inability to limit resource allocation may be the cause.

When the allocation is directly affected by numeric inputs, then fuzzing may produce indications of this weakness.

Effectiveness: Opportunistic

Specialized configuration or tuning may be required to train automated tools to recognize this weakness.

Automated static analysis typically has limited utility in recognizing unlimited allocation problems, except for the missing release of program-independent system resources such as files, sockets, and processes, or unchecked arguments to memory. For system resources, automated static analysis may be able to detect circumstances in which resources are not released after they have expired, or if too much of a resource is requested at once, as can occur with memory. Automated analysis of configuration files may be able to detect settings that do not specify a maximum value.

Automated static analysis tools will not be appropriate for detecting exhaustion of custom resources, such as an intended security policy in which a bulletin board user is only allowed to make a limited number of posts per day.

Strategy: Language Selection

Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

For example, many languages that perform their own memory management, such as Java and Perl, are not subject to buffer overflows. Other languages, such as Ada and C#, typically provide overflow protection, but the protection can be disabled by the programmer.

Be wary that a language's interface to native code may still be subject to overflows, even if the language itself is theoretically safe.

Strategy: Libraries or Frameworks

Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

Examples include the Safe C String Library (SafeStr) by Messier and Viega [REF-57], and the Strsafe.h library from Microsoft [REF-56]. These libraries provide safer versions of overflow-prone string-handling functions.

Strategy: Environment Hardening

Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index checking.

D3-SFCV (Stack Frame Canary Validation) from D3FEND [REF-1334] discusses canary-based detection in detail.

Effectiveness: Defense in Depth

This is not necessarily a complete solution, since these mechanisms only detect certain types of overflows. In addition, the result is still a denial of service, since the typical response is to exit the application.

Consider adhering to the following rules when allocating and managing an application's memory:

• Double check that the buffer is as large as specified.
• When using functions that accept a number of bytes to copy, such as strncpy(), be aware that if the destination buffer size is equal to the source buffer size, it may not NULL-terminate the string.
• Check buffer boundaries if accessing the buffer in a loop and make sure there is no danger of writing past the allocated space.
• If necessary, truncate all input strings to a reasonable length before passing them to the copy and concatenation functions.

Strategy: Environment Hardening

Run or compile the software using features or extensions that randomly arrange the positions of a program's executable and libraries in memory. Because this makes the addresses unpredictable, it can prevent an attacker from reliably jumping to exploitable code.

Examples include Address Space Layout Randomization (ASLR) [REF-58] [REF-60] and Position-Independent Executables (PIE) [REF-64]. Imported modules may be similarly realigned if their default memory addresses conflict with other modules, in a process known as "rebasing" (for Windows) and "prelinking" (for Linux) [REF-1332] using randomly generated addresses. ASLR for libraries cannot be used in conjunction with prelink since it would require relocating the libraries at run-time, defeating the whole purpose of prelinking.

For more information on these techniques see D3-SAOR (Segment Address Offset Randomization) from D3FEND [REF-1335].

Effectiveness: Defense in Depth

Strategy: Environment Hardening

Use a CPU and operating system that offers Data Execution Protection (using hardware NX or XD bits) or the equivalent techniques that simulate this feature in software, such as PaX [REF-60] [REF-61]. These techniques ensure that any instruction executed is exclusively at a memory address that is part of the code segment.

For more information on these techniques see D3-PSEP (Process Segment Execution Prevention) from D3FEND [REF-1336].

Effectiveness: Defense in Depth

Strategy: Environment Hardening

Strategy: Sandbox or Jail

Run the code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which files can be accessed in a particular directory or which commands can be executed by the software.

OS-level examples include the Unix chroot jail, AppArmor, and SELinux. In general, managed code may provide some protection. For example, java.io.FilePermission in the Java SecurityManager allows the software to specify restrictions on file operations.

This may not be a feasible solution, and it only limits the impact to the operating system; the rest of the application may still be subject to compromise.

Be careful to avoid CWE-243 and other weaknesses related to jails.

Effectiveness: Limited

This weakness can often be detected using automated static analysis tools. Many modern tools use data flow analysis or constraint-based techniques to minimize the number of false positives.

Automated static analysis generally does not account for environmental considerations when reporting out-of-bounds memory operations. This can make it difficult for users to determine which warnings should be investigated first. For example, an analysis tool might report buffer overflows that originate from command line arguments in a program that is not expected to run with setuid or other special privileges.

Effectiveness: High

Effectiveness: Moderate

Strategy: Language Selection

Use a language that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

For example, many languages that perform their own memory management, such as Java and Perl, are not subject to buffer overflows. Other languages, such as Ada and C#, typically provide overflow protection, but the protection can be disabled by the programmer.

Be wary that a language's interface to native code may still be subject to overflows, even if the language itself is theoretically safe.

Strategy: Libraries or Frameworks

Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

Examples include the Safe C String Library (SafeStr) by Messier and Viega [REF-57], and the Strsafe.h library from Microsoft [REF-56]. These libraries provide safer versions of overflow-prone string-handling functions.

Strategy: Environment Hardening

Use automatic buffer overflow detection mechanisms that are offered by certain compilers or compiler extensions. Examples include: the Microsoft Visual Studio /GS flag, Fedora/Red Hat FORTIFY_SOURCE GCC flag, StackGuard, and ProPolice, which provide various mechanisms including canary-based detection and range/index checking.

D3-SFCV (Stack Frame Canary Validation) from D3FEND [REF-1334] discusses canary-based detection in detail.

Effectiveness: Defense in Depth

This is not necessarily a complete solution, since these mechanisms only detect certain types of overflows. In addition, the result is still a denial of service, since the typical response is to exit the application.

Consider adhering to the following rules when allocating and managing an application's memory:

• Double check that your buffer is as large as you specify.
• When using functions that accept a number of bytes to copy, such as strncpy(), be aware that if the destination buffer size is equal to the source buffer size, it may not NULL-terminate the string.
• Check buffer boundaries if accessing the buffer in a loop and make sure there is no danger of writing past the allocated space.
• If necessary, truncate all input strings to a reasonable length before passing them to the copy and concatenation functions.

Strategy: Input Validation

Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.

When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."

Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

Strategy: Environment Hardening

Run or compile the software using features or extensions that randomly arrange the positions of a program's executable and libraries in memory. Because this makes the addresses unpredictable, it can prevent an attacker from reliably jumping to exploitable code.

Examples include Address Space Layout Randomization (ASLR) [REF-58] [REF-60] and Position-Independent Executables (PIE) [REF-64]. Imported modules may be similarly realigned if their default memory addresses conflict with other modules, in a process known as "rebasing" (for Windows) and "prelinking" (for Linux) [REF-1332] using randomly generated addresses. ASLR for libraries cannot be used in conjunction with prelink since it would require relocating the libraries at run-time, defeating the whole purpose of prelinking.

For more information on these techniques see D3-SAOR (Segment Address Offset Randomization) from D3FEND [REF-1335].

Effectiveness: Defense in Depth

Strategy: Environment Hardening

Use a CPU and operating system that offers Data Execution Protection (using hardware NX or XD bits) or the equivalent techniques that simulate this feature in software, such as PaX [REF-60] [REF-61]. These techniques ensure that any instruction executed is exclusively at a memory address that is part of the code segment.

For more information on these techniques see D3-PSEP (Process Segment Execution Prevention) from D3FEND [REF-1336].

Effectiveness: Defense in Depth

Effectiveness: Moderate

Strategy: Enforcement by Conversion

Strategy: Environment Hardening

Strategy: Sandbox or Jail

Run the code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which files can be accessed in a particular directory or which commands can be executed by the software.

OS-level examples include the Unix chroot jail, AppArmor, and SELinux. In general, managed code may provide some protection. For example, java.io.FilePermission in the Java SecurityManager allows the software to specify restrictions on file operations.

This may not be a feasible solution, and it only limits the impact to the operating system; the rest of the application may still be subject to compromise.

Be careful to avoid CWE-243 and other weaknesses related to jails.

Effectiveness: Limited

This weakness can often be detected using automated static analysis tools. Many modern tools use data flow analysis or constraint-based techniques to minimize the number of false positives.

Automated static analysis generally does not account for environmental considerations when reporting out-of-bounds memory operations. This can make it difficult for users to determine which warnings should be investigated first. For example, an analysis tool might report buffer overflows that originate from command line arguments in a program that is not expected to run with setuid or other special privileges.

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

Minimize the usage of shared resources in order to remove as much complexity as possible from the control flow and to reduce the likelihood of unexpected conditions occurring.

Additionally, this will minimize the amount of synchronization necessary and may even help to reduce the likelihood of a denial of service where an attacker may be able to repeatedly trigger a critical section (CWE-400).

Strategy: Environment Hardening

This weakness can be detected using dynamic tools and techniques that interact with the software using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The software's operation may slow down, but it should not become unstable, crash, or generate incorrect results.

Race conditions may be detected with a stress-test by calling the software simultaneously from a large number of threads or processes, and look for evidence of any unexpected behavior.

Insert breakpoints or delays in between relevant code statements to artificially expand the race window so that it will be easier to detect.

Effectiveness: Moderate

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

Strategy: Libraries or Frameworks

Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.

For example, use anti-CSRF packages such as the OWASP CSRFGuard. [REF-330]

Another example is the ESAPI Session Management control, which includes a component for CSRF. [REF-45]

Use the "double-submitted cookie" method as described by Felten and Zeller:

When a user visits a site, the site should generate a pseudorandom value and set it as a cookie on the user's machine. The site should require every form submission to include this value as a form value and also as a cookie value. When a POST request is sent to the site, the request should only be considered valid if the form value and the cookie value are the same.

Because of the same-origin policy, an attacker cannot read or modify the value stored in the cookie. To successfully submit a form on behalf of the user, the attacker would have to correctly guess the pseudorandom value. If the pseudorandom value is cryptographically strong, this will be prohibitively difficult.

This technique requires Javascript, so it may not work for browsers that have Javascript disabled. [REF-331]

This weakness can be detected using tools and techniques that require manual (human) analysis, such as penetration testing, threat modeling, and interactive tools that allow the tester to record and modify an active session.

Specifically, manual analysis can be useful for finding this weakness, and for minimizing false positives assuming an understanding of business logic. However, it might not achieve desired code coverage within limited time constraints. For black-box analysis, if credentials are not known for privileged accounts, then the most security-critical portions of the application may not receive sufficient attention.

Consider using OWASP CSRFTester to identify potential issues and aid in manual analysis.

Effectiveness: High

Effectiveness: Limited

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: High

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial

According to SOAR, the following detection techniques may be useful:

Effectiveness: SOAR Partial